Aggregated bundle aether-sft-v1-sources
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- .gitattributes +10 -0
- AI-MO__NuminaMath-1.5/.gitattributes +59 -0
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- SOURCES.md +19 -0
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- allenai__WildChat-1M/data/train-00009-of-00014.parquet +3 -0
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AI-MO__NuminaMath-1.5/README.md
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---
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| 2 |
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license: apache-2.0
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task_categories:
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- text-generation
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language:
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- en
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tags:
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- math
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- post-training
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pretty_name: NuminaMath 1.5
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---
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# Dataset Card for NuminaMath 1.5
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## Dataset Description
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| 16 |
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- **Homepage:** https://projectnumina.ai
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- **Repository:**
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- **Paper:** https://github.com/project-numina/aimo-progress-prize/blob/main/report/numina_dataset.pdf
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- **Leaderboard:**
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- **Point of Contact:** [Jia Li](jia@projectnumina.ai)
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### Dataset Summary
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This is the second iteration of the popular [NuminaMath](https://huggingface.co/datasets/AI-MO/NuminaMath-CoT) dataset, bringing high quality post-training data for approximately 900k competition-level math problems. Each solution is formatted in a Chain of Thought (CoT) manner. The sources of the dataset range from Chinese high school math exercises to US and international mathematics olympiad competition problems. The data were primarily collected from online exam paper PDFs and mathematics discussion forums.
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### What's new?
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| 29 |
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#### Problem metadata
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| 31 |
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After understanding the importance of verifiable output for each problem, we have added `answer`, `problem_type`, `question_type` metadata for all problems:
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| 33 |
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- `answer`: Final answer of the problem when `question_type` is a "math word problem", i.e. a number-valued output. For problems which do not belong to this category, `answer` takes one of the following special values:
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- `proof`: When the `question_type` is proof
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- `notfound`: When we cannot find the answer from the `ref_solution`
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- `problem_type`: The mathematical domain of the problem. See `find_problem_type` for more information. Here are the supported types:
|
| 38 |
+
- Algebra
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| 39 |
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- Geometry
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| 40 |
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- Number Theory
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| 41 |
+
- Combinatorics
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| 42 |
+
- Calculus
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| 43 |
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- Inequalities
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| 44 |
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- Logic and Puzzles
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| 45 |
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- Other
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| 46 |
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- `question_type`: The form or style of the mathematical problem.
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| 47 |
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- multiple-choice question (MCQ)
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| 48 |
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- proof
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| 49 |
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- math-word-problem (problem with output)
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| 50 |
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| 51 |
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#### Some new data (more to come)
|
| 52 |
+
|
| 53 |
+
- Olympiads Reference (source: olympiads ref). After the publication of the first [NuminaMath](https://huggingface.co/datasets/AI-MO/NuminaMath-CoT) dataset, we realized that there are a lot of parsing issues with the `olympiads` subset, due to the use of generic regular experessions and LLMs. To fix this, we have used the official websites from dozens of national Math Olympiads to perform manual parsing and verification of the problems and solutions.
|
| 54 |
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- More manual curated data. `cn_contest`, `inequalities` and `number_theory` are manually curated competition problems provided by our data partners.
|
| 55 |
+
- Removal of synthetic dataset `synthetic_amc`. In our ablation study, this hurt a bit the performance. In the futhur we planned to remove all synthetic data until we find a way to reliably generate high-quality synthetic problems.
|
| 56 |
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### Source breakdown
|
| 59 |
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|
| 60 |
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| source | problems | question_type:proof | question_type:mcq | question_type:word |
|
| 61 |
+
|:---------------|-----------:|----------------------:|--------------------:|---------------------:|
|
| 62 |
+
| olympiads | 197084 | 62970 | 13529 | 117845 |
|
| 63 |
+
| olympiads_ref | 3638 | 2246 | nan | 1392 |
|
| 64 |
+
| amc_aime | 5872 | 208 | 4374 | 963 |
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| 65 |
+
| aops_forum | 67841 | 24532 | 5924 | 33486 |
|
| 66 |
+
| cn_contest | 29944 | 8663 | 5602 | 15649 |
|
| 67 |
+
| inequalities | 7314 | 5780 | 49 | 1478 |
|
| 68 |
+
| number_theory | 4043 | 2591 | 15 | 1239 |
|
| 69 |
+
| cn_k12 | 268819 | 3966 | 115800 | 149010 |
|
| 70 |
+
| orca_math | 151934 | 1 | 17 | 151916 |
|
| 71 |
+
| synthetic_math | 148712 | 41 | 1057 | 147612 |
|
| 72 |
+
| metamath | 11014 | nan | 82 | 10932 |
|
| 73 |
+
| Total | 896215 | 110998 | 146449 | 631522 |
|
| 74 |
+
|
| 75 |
+
### Licensing Information
|
| 76 |
+
|
| 77 |
+
The dataset is available under the [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
|
| 78 |
+
|
| 79 |
+
### Citation Information
|
| 80 |
+
|
| 81 |
+
```
|
| 82 |
+
@misc{numina_math_datasets,
|
| 83 |
+
author = {Jia LI and Edward Beeching and Lewis Tunstall and Ben Lipkin and Roman Soletskyi and Shengyi Costa Huang and Kashif Rasul and Longhui Yu and Albert Jiang and Ziju Shen and Zihan Qin and Bin Dong and Li Zhou and Yann Fleureau and Guillaume Lample and Stanislas Polu},
|
| 84 |
+
title = {NuminaMath},
|
| 85 |
+
year = {2024},
|
| 86 |
+
publisher = {Numina},
|
| 87 |
+
journal = {Hugging Face repository},
|
| 88 |
+
howpublished = {\url{[https://huggingface.co/datasets/AI-MO/NuminaMath-1.5](https://github.com/project-numina/aimo-progress-prize/blob/main/report/numina_dataset.pdf)}}
|
| 89 |
+
}
|
| 90 |
+
```
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ckpt filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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+
*.gz filter=lfs diff=lfs merge=lfs -text
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| 8 |
+
*.h5 filter=lfs diff=lfs merge=lfs -text
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| 9 |
+
*.joblib filter=lfs diff=lfs merge=lfs -text
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| 10 |
+
*.lfs.* filter=lfs diff=lfs merge=lfs -text
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| 11 |
+
*.lz4 filter=lfs diff=lfs merge=lfs -text
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| 12 |
+
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
| 13 |
+
*.model filter=lfs diff=lfs merge=lfs -text
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| 14 |
+
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 15 |
+
*.npy filter=lfs diff=lfs merge=lfs -text
|
| 16 |
+
*.npz filter=lfs diff=lfs merge=lfs -text
|
| 17 |
+
*.onnx filter=lfs diff=lfs merge=lfs -text
|
| 18 |
+
*.ot filter=lfs diff=lfs merge=lfs -text
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| 19 |
+
*.parquet filter=lfs diff=lfs merge=lfs -text
|
| 20 |
+
*.pb filter=lfs diff=lfs merge=lfs -text
|
| 21 |
+
*.pickle filter=lfs diff=lfs merge=lfs -text
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| 22 |
+
*.pkl filter=lfs diff=lfs merge=lfs -text
|
| 23 |
+
*.pt filter=lfs diff=lfs merge=lfs -text
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| 24 |
+
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 25 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
| 26 |
+
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
| 27 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
| 28 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
| 29 |
+
*.tar filter=lfs diff=lfs merge=lfs -text
|
| 30 |
+
*.tflite filter=lfs diff=lfs merge=lfs -text
|
| 31 |
+
*.tgz filter=lfs diff=lfs merge=lfs -text
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| 32 |
+
*.wasm filter=lfs diff=lfs merge=lfs -text
|
| 33 |
+
*.xz filter=lfs diff=lfs merge=lfs -text
|
| 34 |
+
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 35 |
+
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
# Audio files - uncompressed
|
| 38 |
+
*.pcm filter=lfs diff=lfs merge=lfs -text
|
| 39 |
+
*.sam filter=lfs diff=lfs merge=lfs -text
|
| 40 |
+
*.raw filter=lfs diff=lfs merge=lfs -text
|
| 41 |
+
# Audio files - compressed
|
| 42 |
+
*.aac filter=lfs diff=lfs merge=lfs -text
|
| 43 |
+
*.flac filter=lfs diff=lfs merge=lfs -text
|
| 44 |
+
*.mp3 filter=lfs diff=lfs merge=lfs -text
|
| 45 |
+
*.ogg filter=lfs diff=lfs merge=lfs -text
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| 46 |
+
*.wav filter=lfs diff=lfs merge=lfs -text
|
| 47 |
+
# Image files - uncompressed
|
| 48 |
+
*.bmp filter=lfs diff=lfs merge=lfs -text
|
| 49 |
+
*.gif filter=lfs diff=lfs merge=lfs -text
|
| 50 |
+
*.png filter=lfs diff=lfs merge=lfs -text
|
| 51 |
+
*.tiff filter=lfs diff=lfs merge=lfs -text
|
| 52 |
+
# Image files - compressed
|
| 53 |
+
*.jpg filter=lfs diff=lfs merge=lfs -text
|
| 54 |
+
*.jpeg filter=lfs diff=lfs merge=lfs -text
|
| 55 |
+
*.webp filter=lfs diff=lfs merge=lfs -text
|
AI-MO__NuminaMath-CoT/README.md
ADDED
|
@@ -0,0 +1,89 @@
|
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|
|
| 1 |
+
---
|
| 2 |
+
dataset_info:
|
| 3 |
+
features:
|
| 4 |
+
- name: source
|
| 5 |
+
dtype: string
|
| 6 |
+
- name: problem
|
| 7 |
+
dtype: string
|
| 8 |
+
- name: solution
|
| 9 |
+
dtype: string
|
| 10 |
+
- name: messages
|
| 11 |
+
list:
|
| 12 |
+
- name: content
|
| 13 |
+
dtype: string
|
| 14 |
+
- name: role
|
| 15 |
+
dtype: string
|
| 16 |
+
splits:
|
| 17 |
+
- name: train
|
| 18 |
+
num_bytes: 2495457595.0398345
|
| 19 |
+
num_examples: 859494
|
| 20 |
+
- name: test
|
| 21 |
+
num_bytes: 290340.31593470514
|
| 22 |
+
num_examples: 100
|
| 23 |
+
download_size: 1234351634
|
| 24 |
+
dataset_size: 2495747935.355769
|
| 25 |
+
configs:
|
| 26 |
+
- config_name: default
|
| 27 |
+
data_files:
|
| 28 |
+
- split: train
|
| 29 |
+
path: data/train-*
|
| 30 |
+
- split: test
|
| 31 |
+
path: data/test-*
|
| 32 |
+
license: apache-2.0
|
| 33 |
+
task_categories:
|
| 34 |
+
- text-generation
|
| 35 |
+
language:
|
| 36 |
+
- en
|
| 37 |
+
tags:
|
| 38 |
+
- aimo
|
| 39 |
+
- math
|
| 40 |
+
pretty_name: NuminaMath CoT
|
| 41 |
+
---
|
| 42 |
+
|
| 43 |
+
# Dataset Card for NuminaMath CoT
|
| 44 |
+
|
| 45 |
+
## Dataset Description
|
| 46 |
+
|
| 47 |
+
- **Homepage:** https://projectnumina.ai
|
| 48 |
+
- **Repository:** https://github.com/project-numina/aimo-progress-prize
|
| 49 |
+
- **Paper:** https://github.com/project-numina/aimo-progress-prize/blob/main/report/numina_dataset.pdf
|
| 50 |
+
- **Leaderboard:**
|
| 51 |
+
- **Point of Contact:** [Jia Li](jia@projectnumina.ai)
|
| 52 |
+
|
| 53 |
+
|
| 54 |
+
### Dataset Summary
|
| 55 |
+
|
| 56 |
+
Approximately 860k math problems, where each solution is formatted in a Chain of Thought (CoT) manner. The sources of the dataset range from Chinese high school math exercises to US and international mathematics olympiad competition problems. The data were primarily collected from online exam paper PDFs and mathematics discussion forums. The processing steps include (a) OCR from the original PDFs, (b) segmentation into problem-solution pairs, (c) Translation into English, (d) realignment to produce a CoT reasoning format, and (e) final answer formatting.
|
| 57 |
+
|
| 58 |
+
|
| 59 |
+
### Source breakdown
|
| 60 |
+
|
| 61 |
+
| Source | Number of Samples |
|
| 62 |
+
| --- | --- |
|
| 63 |
+
| aops_forum | 30201 |
|
| 64 |
+
| amc_aime | 4072 |
|
| 65 |
+
| cn_k12 | 276591 |
|
| 66 |
+
| gsm8k | 7345 |
|
| 67 |
+
| math | 7478 |
|
| 68 |
+
| olympiads | 150581 |
|
| 69 |
+
| orca_math | 153334 |
|
| 70 |
+
| synthetic_amc | 62111 |
|
| 71 |
+
| synthetic_math | 167895 |
|
| 72 |
+
| **Total** | **859608** |
|
| 73 |
+
|
| 74 |
+
### Licensing Information
|
| 75 |
+
|
| 76 |
+
The dataset is available under the [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
|
| 77 |
+
|
| 78 |
+
### Citation Information
|
| 79 |
+
|
| 80 |
+
```
|
| 81 |
+
@misc{numina_math_datasets,
|
| 82 |
+
author = {Jia LI and Edward Beeching and Lewis Tunstall and Ben Lipkin and Roman Soletskyi and Shengyi Costa Huang and Kashif Rasul and Longhui Yu and Albert Jiang and Ziju Shen and Zihan Qin and Bin Dong and Li Zhou and Yann Fleureau and Guillaume Lample and Stanislas Polu},
|
| 83 |
+
title = {NuminaMath},
|
| 84 |
+
year = {2024},
|
| 85 |
+
publisher = {Numina},
|
| 86 |
+
journal = {Hugging Face repository},
|
| 87 |
+
howpublished = {\url{[https://huggingface.co/AI-MO/NuminaMath-CoT](https://github.com/project-numina/aimo-progress-prize/blob/main/report/numina_dataset.pdf)}}
|
| 88 |
+
}
|
| 89 |
+
```
|
AI-MO__NuminaMath-CoT/data/test-00000-of-00001.parquet
ADDED
|
@@ -0,0 +1,3 @@
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|
|
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AI-MO__NuminaMath-CoT/data/train-00000-of-00005.parquet
ADDED
|
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|
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ADDED
|
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AI-MO__NuminaMath-CoT/data/train-00002-of-00005.parquet
ADDED
|
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| 1 |
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|
| 3 |
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|
AI-MO__NuminaMath-CoT/data/train-00003-of-00005.parquet
ADDED
|
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| 1 |
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|
| 3 |
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|
AI-MO__NuminaMath-CoT/data/train-00004-of-00005.parquet
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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|
| 3 |
+
size 246931989
|
AI-MO__NuminaMath-TIR/.gitattributes
ADDED
|
@@ -0,0 +1,55 @@
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|
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|
|
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|
|
|
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|
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|
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|
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|
|
|
|
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|
|
|
|
|
|
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|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
*.7z filter=lfs diff=lfs merge=lfs -text
|
| 2 |
+
*.arrow filter=lfs diff=lfs merge=lfs -text
|
| 3 |
+
*.bin filter=lfs diff=lfs merge=lfs -text
|
| 4 |
+
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
| 5 |
+
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
| 6 |
+
*.ftz filter=lfs diff=lfs merge=lfs -text
|
| 7 |
+
*.gz filter=lfs diff=lfs merge=lfs -text
|
| 8 |
+
*.h5 filter=lfs diff=lfs merge=lfs -text
|
| 9 |
+
*.joblib filter=lfs diff=lfs merge=lfs -text
|
| 10 |
+
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
| 11 |
+
*.lz4 filter=lfs diff=lfs merge=lfs -text
|
| 12 |
+
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
| 13 |
+
*.model filter=lfs diff=lfs merge=lfs -text
|
| 14 |
+
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 15 |
+
*.npy filter=lfs diff=lfs merge=lfs -text
|
| 16 |
+
*.npz filter=lfs diff=lfs merge=lfs -text
|
| 17 |
+
*.onnx filter=lfs diff=lfs merge=lfs -text
|
| 18 |
+
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 19 |
+
*.parquet filter=lfs diff=lfs merge=lfs -text
|
| 20 |
+
*.pb filter=lfs diff=lfs merge=lfs -text
|
| 21 |
+
*.pickle filter=lfs diff=lfs merge=lfs -text
|
| 22 |
+
*.pkl filter=lfs diff=lfs merge=lfs -text
|
| 23 |
+
*.pt filter=lfs diff=lfs merge=lfs -text
|
| 24 |
+
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 25 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
| 26 |
+
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
| 27 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
| 28 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
| 29 |
+
*.tar filter=lfs diff=lfs merge=lfs -text
|
| 30 |
+
*.tflite filter=lfs diff=lfs merge=lfs -text
|
| 31 |
+
*.tgz filter=lfs diff=lfs merge=lfs -text
|
| 32 |
+
*.wasm filter=lfs diff=lfs merge=lfs -text
|
| 33 |
+
*.xz filter=lfs diff=lfs merge=lfs -text
|
| 34 |
+
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 35 |
+
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
# Audio files - uncompressed
|
| 38 |
+
*.pcm filter=lfs diff=lfs merge=lfs -text
|
| 39 |
+
*.sam filter=lfs diff=lfs merge=lfs -text
|
| 40 |
+
*.raw filter=lfs diff=lfs merge=lfs -text
|
| 41 |
+
# Audio files - compressed
|
| 42 |
+
*.aac filter=lfs diff=lfs merge=lfs -text
|
| 43 |
+
*.flac filter=lfs diff=lfs merge=lfs -text
|
| 44 |
+
*.mp3 filter=lfs diff=lfs merge=lfs -text
|
| 45 |
+
*.ogg filter=lfs diff=lfs merge=lfs -text
|
| 46 |
+
*.wav filter=lfs diff=lfs merge=lfs -text
|
| 47 |
+
# Image files - uncompressed
|
| 48 |
+
*.bmp filter=lfs diff=lfs merge=lfs -text
|
| 49 |
+
*.gif filter=lfs diff=lfs merge=lfs -text
|
| 50 |
+
*.png filter=lfs diff=lfs merge=lfs -text
|
| 51 |
+
*.tiff filter=lfs diff=lfs merge=lfs -text
|
| 52 |
+
# Image files - compressed
|
| 53 |
+
*.jpg filter=lfs diff=lfs merge=lfs -text
|
| 54 |
+
*.jpeg filter=lfs diff=lfs merge=lfs -text
|
| 55 |
+
*.webp filter=lfs diff=lfs merge=lfs -text
|
AI-MO__NuminaMath-TIR/README.md
ADDED
|
@@ -0,0 +1,71 @@
|
|
|
|
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|
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|
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|
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|
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|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- en
|
| 4 |
+
license: apache-2.0
|
| 5 |
+
task_categories:
|
| 6 |
+
- text-generation
|
| 7 |
+
pretty_name: NuminaMath TIR
|
| 8 |
+
dataset_info:
|
| 9 |
+
features:
|
| 10 |
+
- name: problem
|
| 11 |
+
dtype: string
|
| 12 |
+
- name: solution
|
| 13 |
+
dtype: string
|
| 14 |
+
- name: messages
|
| 15 |
+
list:
|
| 16 |
+
- name: content
|
| 17 |
+
dtype: string
|
| 18 |
+
- name: role
|
| 19 |
+
dtype: string
|
| 20 |
+
splits:
|
| 21 |
+
- name: train
|
| 22 |
+
num_bytes: 327147067
|
| 23 |
+
num_examples: 72441
|
| 24 |
+
- name: test
|
| 25 |
+
num_bytes: 461331
|
| 26 |
+
num_examples: 99
|
| 27 |
+
download_size: 147557990
|
| 28 |
+
dataset_size: 327608398
|
| 29 |
+
configs:
|
| 30 |
+
- config_name: default
|
| 31 |
+
data_files:
|
| 32 |
+
- split: train
|
| 33 |
+
path: data/train-*
|
| 34 |
+
- split: test
|
| 35 |
+
path: data/test-*
|
| 36 |
+
tags:
|
| 37 |
+
- math
|
| 38 |
+
- aimo
|
| 39 |
+
---
|
| 40 |
+
|
| 41 |
+
# Dataset Card for NuminaMath CoT
|
| 42 |
+
|
| 43 |
+
## Dataset Description
|
| 44 |
+
|
| 45 |
+
- **Homepage:** https://projectnumina.ai
|
| 46 |
+
- **Repository:** https://github.com/project-numina/aimo-progress-prize
|
| 47 |
+
- **Paper:** https://github.com/project-numina/aimo-progress-prize/blob/main/report/numina_dataset.pdf
|
| 48 |
+
- **Leaderboard:**
|
| 49 |
+
- **Point of Contact:** [Jia Li](jia@projectnumina.ai)
|
| 50 |
+
|
| 51 |
+
|
| 52 |
+
### Dataset Summary
|
| 53 |
+
|
| 54 |
+
Tool-integrated reasoning (TIR) plays a crucial role in this competition. However, collecting and annotating such data is both costly and time-consuming. To address this, we selected approximately 70k problems from the NuminaMath-CoT dataset, focusing on those with numerical outputs, most of which are integers. We then utilized a pipeline leveraging GPT-4 to generate TORA-like reasoning paths, executing the code and producing results until the solution was complete. We filtered out solutions where the final answer did not match the reference and repeated this process three times to ensure accuracy and consistency. This iterative approach allowed us to generate high-quality TORA data efficiently.
|
| 55 |
+
|
| 56 |
+
### Licensing Information
|
| 57 |
+
|
| 58 |
+
The dataset is available under the [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
|
| 59 |
+
|
| 60 |
+
### Citation Information
|
| 61 |
+
|
| 62 |
+
```
|
| 63 |
+
@misc{numina_math_datasets,
|
| 64 |
+
author = {Jia LI, Edward Beeching, Lewis Tunstall, Ben Lipkin, Roman Soletskyi, Shengyi Costa Huang, Kashif Rasul, Longhui Yu, Albert Jiang, Ziju Shen, Zihan Qin, Bin Dong, Li Zhou, Yann Fleureau, Guillaume Lample, and Stanislas Polu},
|
| 65 |
+
title = {NuminaMath TIR},
|
| 66 |
+
year = {2024},
|
| 67 |
+
publisher = {Numina},
|
| 68 |
+
journal = {Hugging Face repository},
|
| 69 |
+
howpublished = {\url{[https://huggingface.co/AI-MO/NuminaMath-TIR](https://github.com/project-numina/aimo-progress-prize/blob/main/report/numina_dataset.pdf)}}
|
| 70 |
+
}
|
| 71 |
+
```
|
AI-MO__NuminaMath-TIR/data/test-00000-of-00001.parquet
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c563eac44e004697447e78470e414c255f8c450478772a84173886daa24039c0
|
| 3 |
+
size 215035
|
AI-MO__NuminaMath-TIR/data/train-00000-of-00001.parquet
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:66163f9fdf2220fed2116142781fe7019a117191e7f08a3339a70a98401061d8
|
| 3 |
+
size 147342955
|
QuixiAI__dolphin-r1/.gitattributes
ADDED
|
@@ -0,0 +1,62 @@
|
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|
| 1 |
+
*.7z filter=lfs diff=lfs merge=lfs -text
|
| 2 |
+
*.arrow filter=lfs diff=lfs merge=lfs -text
|
| 3 |
+
*.bin filter=lfs diff=lfs merge=lfs -text
|
| 4 |
+
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
| 5 |
+
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
| 6 |
+
*.ftz filter=lfs diff=lfs merge=lfs -text
|
| 7 |
+
*.gz filter=lfs diff=lfs merge=lfs -text
|
| 8 |
+
*.h5 filter=lfs diff=lfs merge=lfs -text
|
| 9 |
+
*.joblib filter=lfs diff=lfs merge=lfs -text
|
| 10 |
+
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
| 11 |
+
*.lz4 filter=lfs diff=lfs merge=lfs -text
|
| 12 |
+
*.mds filter=lfs diff=lfs merge=lfs -text
|
| 13 |
+
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
| 14 |
+
*.model filter=lfs diff=lfs merge=lfs -text
|
| 15 |
+
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 16 |
+
*.npy filter=lfs diff=lfs merge=lfs -text
|
| 17 |
+
*.npz filter=lfs diff=lfs merge=lfs -text
|
| 18 |
+
*.onnx filter=lfs diff=lfs merge=lfs -text
|
| 19 |
+
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 20 |
+
*.parquet filter=lfs diff=lfs merge=lfs -text
|
| 21 |
+
*.pb filter=lfs diff=lfs merge=lfs -text
|
| 22 |
+
*.pickle filter=lfs diff=lfs merge=lfs -text
|
| 23 |
+
*.pkl filter=lfs diff=lfs merge=lfs -text
|
| 24 |
+
*.pt filter=lfs diff=lfs merge=lfs -text
|
| 25 |
+
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 26 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
| 27 |
+
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
| 28 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
| 29 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
| 30 |
+
*.tar filter=lfs diff=lfs merge=lfs -text
|
| 31 |
+
*.tflite filter=lfs diff=lfs merge=lfs -text
|
| 32 |
+
*.tgz filter=lfs diff=lfs merge=lfs -text
|
| 33 |
+
*.wasm filter=lfs diff=lfs merge=lfs -text
|
| 34 |
+
*.xz filter=lfs diff=lfs merge=lfs -text
|
| 35 |
+
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 38 |
+
# Audio files - uncompressed
|
| 39 |
+
*.pcm filter=lfs diff=lfs merge=lfs -text
|
| 40 |
+
*.sam filter=lfs diff=lfs merge=lfs -text
|
| 41 |
+
*.raw filter=lfs diff=lfs merge=lfs -text
|
| 42 |
+
# Audio files - compressed
|
| 43 |
+
*.aac filter=lfs diff=lfs merge=lfs -text
|
| 44 |
+
*.flac filter=lfs diff=lfs merge=lfs -text
|
| 45 |
+
*.mp3 filter=lfs diff=lfs merge=lfs -text
|
| 46 |
+
*.ogg filter=lfs diff=lfs merge=lfs -text
|
| 47 |
+
*.wav filter=lfs diff=lfs merge=lfs -text
|
| 48 |
+
# Image files - uncompressed
|
| 49 |
+
*.bmp filter=lfs diff=lfs merge=lfs -text
|
| 50 |
+
*.gif filter=lfs diff=lfs merge=lfs -text
|
| 51 |
+
*.png filter=lfs diff=lfs merge=lfs -text
|
| 52 |
+
*.tiff filter=lfs diff=lfs merge=lfs -text
|
| 53 |
+
# Image files - compressed
|
| 54 |
+
*.jpg filter=lfs diff=lfs merge=lfs -text
|
| 55 |
+
*.jpeg filter=lfs diff=lfs merge=lfs -text
|
| 56 |
+
*.webp filter=lfs diff=lfs merge=lfs -text
|
| 57 |
+
# Video files - compressed
|
| 58 |
+
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
| 59 |
+
*.webm filter=lfs diff=lfs merge=lfs -text
|
| 60 |
+
dolphin-r1-nonreasoning.jsonl filter=lfs diff=lfs merge=lfs -text
|
| 61 |
+
dolphin-r1-reasoning-deepseek.jsonl filter=lfs diff=lfs merge=lfs -text
|
| 62 |
+
dolphin-r1-reasoning-flash.jsonl filter=lfs diff=lfs merge=lfs -text
|
QuixiAI__dolphin-r1/README.md
ADDED
|
@@ -0,0 +1,43 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
configs:
|
| 4 |
+
- config_name: nonreasoning
|
| 5 |
+
data_files:
|
| 6 |
+
- split: train
|
| 7 |
+
path: dolphin-r1-nonreasoning.jsonl
|
| 8 |
+
- config_name: reasoning-deepseek
|
| 9 |
+
data_files:
|
| 10 |
+
- split: train
|
| 11 |
+
path: dolphin-r1-reasoning-deepseek.jsonl
|
| 12 |
+
- config_name: reasoning-flash
|
| 13 |
+
data_files:
|
| 14 |
+
- split: train
|
| 15 |
+
path: dolphin-r1-reasoning-flash.jsonl
|
| 16 |
+
---
|
| 17 |
+
# Dolphin R1 🐬
|
| 18 |
+
|
| 19 |
+
An Apache-2.0 dataset curated by [Eric Hartford](https://huggingface.co/ehartford) and [Cognitive Computations](https://huggingface.co/cognitivecomputations)
|
| 20 |
+
|
| 21 |
+
[](https://discord.gg/cognitivecomputations)
|
| 22 |
+
Discord: https://discord.gg/cognitivecomputations
|
| 23 |
+
|
| 24 |
+
<img src="https://cdn-uploads.huggingface.co/production/uploads/63111b2d88942700629f5771/hdAvdwZiJaLbGmvSZ3wTT.png" width="600" />
|
| 25 |
+
|
| 26 |
+
## Sponsors
|
| 27 |
+
Our appreciation for the generous sponsors of Dolphin R1 - Without whom this dataset could not exist.
|
| 28 |
+
- [Dria](https://dria.co) https://x.com/driaforall - Inference Sponsor (DeepSeek)
|
| 29 |
+
- [Chutes](https://chutes.ai) https://x.com/rayon_labs - Inference Sponsor (Flash)
|
| 30 |
+
- [Crusoe Cloud](https://crusoe.ai/) - Compute Sponsor
|
| 31 |
+
- [Andreessen Horowitz](https://a16z.com/) - provided the [grant](https://a16z.com/supporting-the-open-source-ai-community/) that originally launched Dolphin
|
| 32 |
+
|
| 33 |
+
## Overview
|
| 34 |
+
|
| 35 |
+
We create a 800k sample dataset similar in composition to the one used to train DeepSeek-R1 Distill models.
|
| 36 |
+
|
| 37 |
+
### Dataset Composition
|
| 38 |
+
|
| 39 |
+
- 300k reasoning samples from DeepSeek-R1
|
| 40 |
+
- 300k reasoning samples from Gemini 2.0 flash thinking
|
| 41 |
+
- 200k samples of Dolphin chat.
|
| 42 |
+
|
| 43 |
+
The purpose of this dataset is to train R1-style reasoning models.
|
QuixiAI__dolphin-r1/dolphin-r1-nonreasoning.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
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|
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|
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+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:9a9f3f21965b448f723f02d61198624baae025fdb2186678e7b2e3525cdf175a
|
| 3 |
+
size 1518599155
|
QuixiAI__dolphin-r1/dolphin-r1-reasoning-deepseek.jsonl
ADDED
|
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|
|
|
|
|
|
|
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|
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|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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+
oid sha256:6649b3223199ca9bcdf2f4c44bd417c9b25dcc01e798a7645d4d4976d4a63a8f
|
| 3 |
+
size 3848509571
|
QuixiAI__dolphin-r1/dolphin-r1-reasoning-flash.jsonl
ADDED
|
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|
|
|
|
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|
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+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:850614bd2d50028674495bf17f8ef66c2d9f872e386a8186d0b84f80c1724276
|
| 3 |
+
size 3491037514
|
QuixiAI__dolphin/.gitattributes
ADDED
|
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|
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|
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|
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|
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|
| 13 |
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|
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|
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|
| 16 |
+
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|
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|
| 18 |
+
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 19 |
+
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|
| 20 |
+
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|
| 21 |
+
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|
| 22 |
+
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|
| 23 |
+
*.pt filter=lfs diff=lfs merge=lfs -text
|
| 24 |
+
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 25 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
| 26 |
+
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
| 27 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
| 28 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
| 29 |
+
*.tar filter=lfs diff=lfs merge=lfs -text
|
| 30 |
+
*.tflite filter=lfs diff=lfs merge=lfs -text
|
| 31 |
+
*.tgz filter=lfs diff=lfs merge=lfs -text
|
| 32 |
+
*.wasm filter=lfs diff=lfs merge=lfs -text
|
| 33 |
+
*.xz filter=lfs diff=lfs merge=lfs -text
|
| 34 |
+
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 35 |
+
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
# Audio files - uncompressed
|
| 38 |
+
*.pcm filter=lfs diff=lfs merge=lfs -text
|
| 39 |
+
*.sam filter=lfs diff=lfs merge=lfs -text
|
| 40 |
+
*.raw filter=lfs diff=lfs merge=lfs -text
|
| 41 |
+
# Audio files - compressed
|
| 42 |
+
*.aac filter=lfs diff=lfs merge=lfs -text
|
| 43 |
+
*.flac filter=lfs diff=lfs merge=lfs -text
|
| 44 |
+
*.mp3 filter=lfs diff=lfs merge=lfs -text
|
| 45 |
+
*.ogg filter=lfs diff=lfs merge=lfs -text
|
| 46 |
+
*.wav filter=lfs diff=lfs merge=lfs -text
|
| 47 |
+
# Image files - uncompressed
|
| 48 |
+
*.bmp filter=lfs diff=lfs merge=lfs -text
|
| 49 |
+
*.gif filter=lfs diff=lfs merge=lfs -text
|
| 50 |
+
*.png filter=lfs diff=lfs merge=lfs -text
|
| 51 |
+
*.tiff filter=lfs diff=lfs merge=lfs -text
|
| 52 |
+
# Image files - compressed
|
| 53 |
+
*.jpg filter=lfs diff=lfs merge=lfs -text
|
| 54 |
+
*.jpeg filter=lfs diff=lfs merge=lfs -text
|
| 55 |
+
*.webp filter=lfs diff=lfs merge=lfs -text
|
| 56 |
+
flan1m-alpaca-uncensored.jsonl filter=lfs diff=lfs merge=lfs -text
|
| 57 |
+
flan5m-alpaca-uncensored.jsonl filter=lfs diff=lfs merge=lfs -text
|
| 58 |
+
flan1m-sharegpt-deduped.json filter=lfs diff=lfs merge=lfs -text
|
| 59 |
+
flan5m-sharegpt-deduped.json filter=lfs diff=lfs merge=lfs -text
|
| 60 |
+
flan1m-alpaca-uncensored-deduped.jsonl filter=lfs diff=lfs merge=lfs -text
|
| 61 |
+
flan5m-alpaca-uncensored-deduped.jsonl filter=lfs diff=lfs merge=lfs -text
|
QuixiAI__dolphin/README.md
ADDED
|
@@ -0,0 +1,68 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
|
|
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|
|
|
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|
|
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|
|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
task_categories:
|
| 4 |
+
- text-generation
|
| 5 |
+
language:
|
| 6 |
+
- en
|
| 7 |
+
configs:
|
| 8 |
+
- config_name: flan1m-alpaca-uncensored
|
| 9 |
+
data_files: flan1m-alpaca-uncensored.jsonl
|
| 10 |
+
- config_name: flan5m-alpaca-uncensored
|
| 11 |
+
data_files: flan5m-alpaca-uncensored.jsonl
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
Dolphin 🐬
|
| 15 |
+
|
| 16 |
+
https://erichartford.com/dolphin
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Dataset details
|
| 20 |
+
|
| 21 |
+
This dataset is an attempt to replicate the results of [Microsoft's Orca](https://www.microsoft.com/en-us/research/publication/orca-progressive-learning-from-complex-explanation-traces-of-gpt-4/)
|
| 22 |
+
|
| 23 |
+
Our dataset consists of:
|
| 24 |
+
|
| 25 |
+
- ~1 million of FLANv2 augmented with GPT-4 completions (flan1m-alpaca-uncensored.jsonl)
|
| 26 |
+
- ~3.5 million of FLANv2 augmented with GPT-3.5 completions (flan5m-alpaca-uncensored.jsonl)
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
We followed the submix and system prompt distribution outlined in the Orca paper. With a few exceptions. We included all 75k of CoT in the FLAN-1m dataset rather than sampling that. Also, we found that many items were duplicated, so we removed duplicates, resulting in 3.5m instructs in the ChatGPT dataset.
|
| 30 |
+
|
| 31 |
+
Then we filtered out instances of alignment, refusal, avoidance, and bias, in order to produce an uncensored model upon which can be layered your personalized alignment LoRA.
|
| 32 |
+
|
| 33 |
+
Token distribution for GPT-3.5 completions
|
| 34 |
+
|
| 35 |
+
|
| 36 |
+
### Loading
|
| 37 |
+
```python
|
| 38 |
+
## load GPT-4 completions
|
| 39 |
+
dataset = load_dataset("ehartford/dolphin",data_files="flan1m-alpaca-uncensored.jsonl")
|
| 40 |
+
|
| 41 |
+
## load GPT-3.5 completions
|
| 42 |
+
dataset = load_dataset("ehartford/dolphin",data_files="flan5m-alpaca-uncensored.jsonl")
|
| 43 |
+
```
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
This dataset is licensed apache-2.0 for commercial or non-commercial use.
|
| 47 |
+
|
| 48 |
+
We currently plan to release Dolphin on:
|
| 49 |
+
|
| 50 |
+
- Xgen 7b 8k
|
| 51 |
+
- LLaMA 13b (Non-commercial)
|
| 52 |
+
- MPT 30b 8k
|
| 53 |
+
- LLaMA 33b (Non-commercial)
|
| 54 |
+
- Falcon 40b
|
| 55 |
+
- LLaMA 65b (Non-commercial)
|
| 56 |
+
|
| 57 |
+
The Dolphin models that are released will be subject to the license of the foundational model on which it is trained. (LLaMA releases will be non-commercial)
|
| 58 |
+
|
| 59 |
+
I would like to thank the motley crew of Open Source AI/ML engineers who have worked beside me in this endeavor. Including:
|
| 60 |
+
|
| 61 |
+
- Wing "Caseus" Lian and NanoBit of OpenAccess AI Collective
|
| 62 |
+
- Rohan
|
| 63 |
+
- Teknium
|
| 64 |
+
- Pankaj Mathur
|
| 65 |
+
- Tom "TheBloke" Jobbins for quantizing and amplifying
|
| 66 |
+
- Special thanks to EdenCoder and chirper.ai for mentorship and financial sponsorship.
|
| 67 |
+
- Special thanks to Kilkonie for his very valued mentorship.
|
| 68 |
+
- All the other people in the Open Source AI community who have taught me and helped me along the way.
|
QuixiAI__dolphin/convertToShareGpt.py
ADDED
|
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import argparse
|
| 2 |
+
import jsonlines
|
| 3 |
+
import json
|
| 4 |
+
from tqdm import tqdm
|
| 5 |
+
import uuid
|
| 6 |
+
|
| 7 |
+
parser = argparse.ArgumentParser()
|
| 8 |
+
parser.add_argument(
|
| 9 |
+
"--in-file", type=str, required=True, default="flan5m-alpaca-uncensored.jsonl"
|
| 10 |
+
)
|
| 11 |
+
parser.add_argument(
|
| 12 |
+
"--out-file", type=str, required=True, default="flan5m-sharegpt.json"
|
| 13 |
+
)
|
| 14 |
+
args = parser.parse_args()
|
| 15 |
+
in_file = args.in_file
|
| 16 |
+
out_file = args.out_file
|
| 17 |
+
|
| 18 |
+
f = open(out_file, "w", encoding="utf-8")
|
| 19 |
+
|
| 20 |
+
out = []
|
| 21 |
+
with jsonlines.open(in_file) as reader:
|
| 22 |
+
for obj in tqdm(reader):
|
| 23 |
+
out.append(
|
| 24 |
+
{
|
| 25 |
+
"id": f"{uuid.uuid4()}",
|
| 26 |
+
"bot": "dolphin",
|
| 27 |
+
"training": obj["instruction"],
|
| 28 |
+
"conversations": [
|
| 29 |
+
{"from": "human", "value": obj["input"]},
|
| 30 |
+
{"from": "gpt", "value": obj["output"]},
|
| 31 |
+
],
|
| 32 |
+
}
|
| 33 |
+
)
|
| 34 |
+
json.dump(out, f, ensure_ascii=False)
|
| 35 |
+
f.close()
|
QuixiAI__dolphin/dedupeToShareGpt.py
ADDED
|
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import argparse
|
| 2 |
+
import jsonlines
|
| 3 |
+
import json
|
| 4 |
+
from tqdm import tqdm
|
| 5 |
+
import uuid
|
| 6 |
+
|
| 7 |
+
parser = argparse.ArgumentParser()
|
| 8 |
+
parser.add_argument("--in-file", type=str, default="flan1m-alpaca-uncensored.jsonl")
|
| 9 |
+
parser.add_argument("--out-file", type=str, default="flan1m-sharegpt-deduped.json")
|
| 10 |
+
args = parser.parse_args()
|
| 11 |
+
in_file = args.in_file
|
| 12 |
+
out_file = args.out_file
|
| 13 |
+
|
| 14 |
+
f = open(out_file, "w", encoding="utf-8")
|
| 15 |
+
|
| 16 |
+
questions = {}
|
| 17 |
+
|
| 18 |
+
out = []
|
| 19 |
+
with jsonlines.open(in_file) as reader:
|
| 20 |
+
for obj in tqdm(reader):
|
| 21 |
+
if questions.get(obj["instruction"] + obj["input"]) is None:
|
| 22 |
+
questions[obj["instruction"] + obj["input"]] = True
|
| 23 |
+
out.append(
|
| 24 |
+
{
|
| 25 |
+
"id": f"{uuid.uuid4()}",
|
| 26 |
+
"bot": "dolphin",
|
| 27 |
+
"training": obj["instruction"],
|
| 28 |
+
"conversations": [
|
| 29 |
+
{"from": "human", "value": obj["input"]},
|
| 30 |
+
{"from": "gpt", "value": obj["output"]},
|
| 31 |
+
],
|
| 32 |
+
}
|
| 33 |
+
)
|
| 34 |
+
json.dump(out, f, ensure_ascii=False)
|
| 35 |
+
f.close()
|
QuixiAI__dolphin/flan1m-alpaca-uncensored-deduped.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6b33a04d9d3224eac73e1eb2ba8c0d9702cb2c84a486c699a61ce91682f931ac
|
| 3 |
+
size 1518385578
|
QuixiAI__dolphin/flan1m-alpaca-uncensored.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:91fa1e54f2dfe28ed3c860ef930ebe53b2b92c1d64c461b54e524c18871c5df9
|
| 3 |
+
size 1599597954
|
QuixiAI__dolphin/flan1m-sharegpt-deduped.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1fbb335f49c6dc37c77431878eb3c4d2199c0bf8f833303266906ec2b89a0e64
|
| 3 |
+
size 1616128338
|
QuixiAI__dolphin/flan5m-alpaca-uncensored-deduped.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b258a311e581570b52ab72e7e7e5d40b3ed732bf88191d07d295ece56b0d76aa
|
| 3 |
+
size 4535078254
|
QuixiAI__dolphin/flan5m-alpaca-uncensored.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:205ecc01054c6b747bf4550845536219a4d53e51d4ac255f2892126a0ca722f4
|
| 3 |
+
size 4804910031
|
QuixiAI__dolphin/flan5m-sharegpt-deduped.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:640f24d1a6aaf037126f151643dae3eb27923f071e4a768ede8b3c4447f81062
|
| 3 |
+
size 4839619202
|
QuixiAI__dolphin/fp32_to_fp16.py
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import torch
|
| 2 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM
|
| 3 |
+
import argparse
|
| 4 |
+
import os
|
| 5 |
+
|
| 6 |
+
parser = argparse.ArgumentParser(description="Convert fp32 model to fp16")
|
| 7 |
+
parser.add_argument("model_dir", type=str, help="fp32 model folder")
|
| 8 |
+
parser.add_argument("output_dir", type=str, help="fp16 output folder")
|
| 9 |
+
parser.add_argument("--device", type=str, default="cuda:0", help="device")
|
| 10 |
+
|
| 11 |
+
args = parser.parse_args()
|
| 12 |
+
|
| 13 |
+
model_dir = args.model_dir
|
| 14 |
+
output_dir = args.output_dir
|
| 15 |
+
|
| 16 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 17 |
+
model_dir,
|
| 18 |
+
torch_dtype=torch.float32,
|
| 19 |
+
low_cpu_mem_usage=True,
|
| 20 |
+
trust_remote_code=True,
|
| 21 |
+
)
|
| 22 |
+
|
| 23 |
+
model = model.half()
|
| 24 |
+
|
| 25 |
+
model.save_pretrained(output_dir, torch_dtype=torch.float16)
|
QuixiAI__dolphin/llama_flash_attn_monkey_patch.py
ADDED
|
@@ -0,0 +1,123 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from typing import List, Optional, Tuple
|
| 2 |
+
import logging
|
| 3 |
+
|
| 4 |
+
import torch
|
| 5 |
+
from torch import nn
|
| 6 |
+
|
| 7 |
+
import transformers
|
| 8 |
+
from transformers.models.llama.modeling_llama import apply_rotary_pos_emb
|
| 9 |
+
|
| 10 |
+
from einops import rearrange
|
| 11 |
+
|
| 12 |
+
from flash_attn import (
|
| 13 |
+
flash_attn_varlen_qkvpacked_func,
|
| 14 |
+
)
|
| 15 |
+
from flash_attn.bert_padding import unpad_input, pad_input
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
def forward(
|
| 19 |
+
self,
|
| 20 |
+
hidden_states: torch.Tensor,
|
| 21 |
+
attention_mask: Optional[torch.Tensor] = None,
|
| 22 |
+
position_ids: Optional[torch.Tensor] = None,
|
| 23 |
+
past_key_value: Optional[Tuple[torch.Tensor]] = None,
|
| 24 |
+
output_attentions: bool = False,
|
| 25 |
+
use_cache: bool = False,
|
| 26 |
+
) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
|
| 27 |
+
"""Input shape: Batch x Time x Channel
|
| 28 |
+
|
| 29 |
+
attention_mask: [bsz, q_len]
|
| 30 |
+
"""
|
| 31 |
+
bsz, q_len, _ = hidden_states.size()
|
| 32 |
+
|
| 33 |
+
query_states = (
|
| 34 |
+
self.q_proj(hidden_states)
|
| 35 |
+
.view(bsz, q_len, self.num_heads, self.head_dim)
|
| 36 |
+
.transpose(1, 2)
|
| 37 |
+
)
|
| 38 |
+
key_states = (
|
| 39 |
+
self.k_proj(hidden_states)
|
| 40 |
+
.view(bsz, q_len, self.num_heads, self.head_dim)
|
| 41 |
+
.transpose(1, 2)
|
| 42 |
+
)
|
| 43 |
+
value_states = (
|
| 44 |
+
self.v_proj(hidden_states)
|
| 45 |
+
.view(bsz, q_len, self.num_heads, self.head_dim)
|
| 46 |
+
.transpose(1, 2)
|
| 47 |
+
)
|
| 48 |
+
# [bsz, q_len, nh, hd]
|
| 49 |
+
# [bsz, nh, q_len, hd]
|
| 50 |
+
|
| 51 |
+
kv_seq_len = key_states.shape[-2]
|
| 52 |
+
assert past_key_value is None, "past_key_value is not supported"
|
| 53 |
+
|
| 54 |
+
cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
|
| 55 |
+
query_states, key_states = apply_rotary_pos_emb(
|
| 56 |
+
query_states, key_states, cos, sin, position_ids
|
| 57 |
+
)
|
| 58 |
+
# [bsz, nh, t, hd]
|
| 59 |
+
assert not output_attentions, "output_attentions is not supported"
|
| 60 |
+
assert not use_cache, "use_cache is not supported"
|
| 61 |
+
|
| 62 |
+
# Flash attention codes from
|
| 63 |
+
# https://github.com/HazyResearch/flash-attention/blob/main/flash_attn/flash_attention.py
|
| 64 |
+
|
| 65 |
+
# transform the data into the format required by flash attention
|
| 66 |
+
qkv = torch.stack(
|
| 67 |
+
[query_states, key_states, value_states], dim=2
|
| 68 |
+
) # [bsz, nh, 3, q_len, hd]
|
| 69 |
+
qkv = qkv.transpose(1, 3) # [bsz, q_len, 3, nh, hd]
|
| 70 |
+
# We have disabled _prepare_decoder_attention_mask in LlamaModel
|
| 71 |
+
# the attention_mask should be the same as the key_padding_mask
|
| 72 |
+
key_padding_mask = attention_mask
|
| 73 |
+
|
| 74 |
+
if key_padding_mask is None:
|
| 75 |
+
qkv = rearrange(qkv, "b s ... -> (b s) ...")
|
| 76 |
+
max_s = q_len
|
| 77 |
+
cu_q_lens = torch.arange(
|
| 78 |
+
0, (bsz + 1) * q_len, step=q_len, dtype=torch.int32, device=qkv.device
|
| 79 |
+
)
|
| 80 |
+
output = flash_attn_varlen_qkvpacked_func(
|
| 81 |
+
qkv, cu_q_lens, max_s, 0.0, softmax_scale=None, causal=True
|
| 82 |
+
)
|
| 83 |
+
output = rearrange(output, "(b s) ... -> b s ...", b=bsz)
|
| 84 |
+
else:
|
| 85 |
+
nheads = qkv.shape[-2]
|
| 86 |
+
x = rearrange(qkv, "b s three h d -> b s (three h d)")
|
| 87 |
+
x_unpad, indices, cu_q_lens, max_s = unpad_input(x, key_padding_mask)
|
| 88 |
+
x_unpad = rearrange(
|
| 89 |
+
x_unpad, "nnz (three h d) -> nnz three h d", three=3, h=nheads
|
| 90 |
+
)
|
| 91 |
+
output_unpad = flash_attn_varlen_qkvpacked_func(
|
| 92 |
+
x_unpad, cu_q_lens, max_s, 0.0, softmax_scale=None, causal=True
|
| 93 |
+
)
|
| 94 |
+
output = rearrange(
|
| 95 |
+
pad_input(
|
| 96 |
+
rearrange(output_unpad, "nnz h d -> nnz (h d)"), indices, bsz, q_len
|
| 97 |
+
),
|
| 98 |
+
"b s (h d) -> b s h d",
|
| 99 |
+
h=nheads,
|
| 100 |
+
)
|
| 101 |
+
return self.o_proj(rearrange(output, "b s h d -> b s (h d)")), None, None
|
| 102 |
+
|
| 103 |
+
|
| 104 |
+
# Disable the transformation of the attention mask in LlamaModel as the flash attention
|
| 105 |
+
# requires the attention mask to be the same as the key_padding_mask
|
| 106 |
+
def _prepare_decoder_attention_mask(
|
| 107 |
+
self, attention_mask, input_shape, inputs_embeds, past_key_values_length
|
| 108 |
+
):
|
| 109 |
+
# [bsz, seq_len]
|
| 110 |
+
return attention_mask
|
| 111 |
+
|
| 112 |
+
|
| 113 |
+
def replace_llama_attn_with_flash_attn():
|
| 114 |
+
cuda_major, cuda_minor = torch.cuda.get_device_capability()
|
| 115 |
+
if cuda_major < 8:
|
| 116 |
+
logging.warning(
|
| 117 |
+
"Flash attention is only supported on A100 or H100 GPU during training due to head dim > 64 backward."
|
| 118 |
+
"ref: https://github.com/HazyResearch/flash-attention/issues/190#issuecomment-1523359593"
|
| 119 |
+
)
|
| 120 |
+
transformers.models.llama.modeling_llama.LlamaModel._prepare_decoder_attention_mask = (
|
| 121 |
+
_prepare_decoder_attention_mask
|
| 122 |
+
)
|
| 123 |
+
transformers.models.llama.modeling_llama.LlamaAttention.forward = forward
|
README.md
ADDED
|
@@ -0,0 +1,60 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- instruction-tuning
|
| 5 |
+
- sft
|
| 6 |
+
- generalist
|
| 7 |
+
- math
|
| 8 |
+
- code
|
| 9 |
+
- reasoning
|
| 10 |
+
- conversation
|
| 11 |
+
- chat
|
| 12 |
+
- tulu-3
|
| 13 |
+
- openhermes
|
| 14 |
+
- wildchat
|
| 15 |
+
- dolphin
|
| 16 |
+
- aether-family
|
| 17 |
+
size_categories:
|
| 18 |
+
- 1M<n<10M
|
| 19 |
+
---
|
| 20 |
+
|
| 21 |
+
# aether-sft-v1-sources
|
| 22 |
+
|
| 23 |
+
Top-tier generalist SFT instruction-tuning sources for AETHER training. Aggregates the SOTA datasets: Tulu-3 SFT mixture (Allen AI), OpenHermes-2.5 (Teknium), NuminaMath-CoT/1.5 (AI-MO, math reasoning), WildChat-1M (real GPT-4 conversations), Dolphin + Dolphin-R1 (reasoning), Tulu-3 personas (math/instr). Multi-skill: instruction-following, math reasoning, coding, dialogue, multilingual.
|
| 24 |
+
|
| 25 |
+
## Disclaimer (Responsible Disclosure)
|
| 26 |
+
|
| 27 |
+
This bundle aggregates **publicly available** security research datasets for
|
| 28 |
+
**defensive purposes only**: training detection systems, threat-classification
|
| 29 |
+
models, and security research tools.
|
| 30 |
+
|
| 31 |
+
Do **not** use any artifact in this collection for offensive operations against
|
| 32 |
+
systems you do not own or have explicit authorization to test. See individual
|
| 33 |
+
source licenses in `SOURCES.md`.
|
| 34 |
+
|
| 35 |
+
## Contents
|
| 36 |
+
|
| 37 |
+
This is an aggregation of 11 HuggingFace datasets,
|
| 38 |
+
re-bundled here for reproducibility and convenience. Each source is preserved
|
| 39 |
+
in its original layout under `<owner>__<repo>/`.
|
| 40 |
+
|
| 41 |
+
See `SOURCES.md` for the full per-source attribution table including
|
| 42 |
+
original license, URL, and category.
|
| 43 |
+
|
| 44 |
+
## How to use
|
| 45 |
+
|
| 46 |
+
```python
|
| 47 |
+
from huggingface_hub import snapshot_download
|
| 48 |
+
path = snapshot_download(repo_id="jescy525/aether-sft-v1-sources", repo_type="dataset")
|
| 49 |
+
# path/AlicanKiraz0__Cybersecurity-Dataset-Fenrir-v2.1/
|
| 50 |
+
# path/Trendyol__Trendyol-Cybersecurity-Instruction-Tuning-Dataset/
|
| 51 |
+
# ...
|
| 52 |
+
```
|
| 53 |
+
|
| 54 |
+
## License
|
| 55 |
+
|
| 56 |
+
Multi-license (Apache-2.0 + ODC-BY + MIT). Tulu-3 + WildChat ODC-BY include non-commercial subsets -- see SOURCES.md per dataset.
|
| 57 |
+
|
| 58 |
+
This re-bundled collection is released under Apache-2.0 **for the metadata
|
| 59 |
+
and aggregation layer only** — each individual source retains its original
|
| 60 |
+
license.
|
SOURCES.md
ADDED
|
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Sources — aether-sft-v1-sources
|
| 2 |
+
|
| 3 |
+
| # | Source repo | Category | License | URL |
|
| 4 |
+
|---|---|---|---|---|
|
| 5 |
+
| 1 | `allenai/tulu-3-sft-mixture` | sft-mixture-top | odc-by | https://hf.co/datasets/allenai/tulu-3-sft-mixture |
|
| 6 |
+
| 2 | `teknium/OpenHermes-2.5` | sft-mixture-top | unknown | https://hf.co/datasets/teknium/OpenHermes-2.5 |
|
| 7 |
+
| 3 | `AI-MO/NuminaMath-CoT` | math-cot | apache-2.0 | https://hf.co/datasets/AI-MO/NuminaMath-CoT |
|
| 8 |
+
| 4 | `AI-MO/NuminaMath-1.5` | math-cot | apache-2.0 | https://hf.co/datasets/AI-MO/NuminaMath-1.5 |
|
| 9 |
+
| 5 | `AI-MO/NuminaMath-TIR` | math-tools | apache-2.0 | https://hf.co/datasets/AI-MO/NuminaMath-TIR |
|
| 10 |
+
| 6 | `allenai/WildChat-1M` | real-chat | odc-by | https://hf.co/datasets/allenai/WildChat-1M |
|
| 11 |
+
| 7 | `QuixiAI/dolphin-r1` | reasoning | apache-2.0 | https://hf.co/datasets/QuixiAI/dolphin-r1 |
|
| 12 |
+
| 8 | `QuixiAI/dolphin` | instruction-flan | apache-2.0 | https://hf.co/datasets/QuixiAI/dolphin |
|
| 13 |
+
| 9 | `allenai/tulu-3-sft-personas-instruction-following` | personas-instr | odc-by | https://hf.co/datasets/allenai/tulu-3-sft-personas-instruction-following |
|
| 14 |
+
| 10 | `allenai/tulu-3-sft-personas-math` | personas-math | unknown | https://hf.co/datasets/allenai/tulu-3-sft-personas-math |
|
| 15 |
+
| 11 | `allenai/tulu-3-sft-personas-algebra` | personas-math | unknown | https://hf.co/datasets/allenai/tulu-3-sft-personas-algebra |
|
| 16 |
+
|
| 17 |
+
## Citation
|
| 18 |
+
|
| 19 |
+
If you use this bundle, please cite each individual source per their original citation requirements. This re-bundled collection adds no scientific contribution beyond aggregation and convenience for ASI training workflows.
|
allenai__WildChat-1M/.gitattributes
ADDED
|
@@ -0,0 +1,55 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
*.7z filter=lfs diff=lfs merge=lfs -text
|
| 2 |
+
*.arrow filter=lfs diff=lfs merge=lfs -text
|
| 3 |
+
*.bin filter=lfs diff=lfs merge=lfs -text
|
| 4 |
+
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
| 5 |
+
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
| 6 |
+
*.ftz filter=lfs diff=lfs merge=lfs -text
|
| 7 |
+
*.gz filter=lfs diff=lfs merge=lfs -text
|
| 8 |
+
*.h5 filter=lfs diff=lfs merge=lfs -text
|
| 9 |
+
*.joblib filter=lfs diff=lfs merge=lfs -text
|
| 10 |
+
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
| 11 |
+
*.lz4 filter=lfs diff=lfs merge=lfs -text
|
| 12 |
+
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
| 13 |
+
*.model filter=lfs diff=lfs merge=lfs -text
|
| 14 |
+
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 15 |
+
*.npy filter=lfs diff=lfs merge=lfs -text
|
| 16 |
+
*.npz filter=lfs diff=lfs merge=lfs -text
|
| 17 |
+
*.onnx filter=lfs diff=lfs merge=lfs -text
|
| 18 |
+
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 19 |
+
*.parquet filter=lfs diff=lfs merge=lfs -text
|
| 20 |
+
*.pb filter=lfs diff=lfs merge=lfs -text
|
| 21 |
+
*.pickle filter=lfs diff=lfs merge=lfs -text
|
| 22 |
+
*.pkl filter=lfs diff=lfs merge=lfs -text
|
| 23 |
+
*.pt filter=lfs diff=lfs merge=lfs -text
|
| 24 |
+
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 25 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
| 26 |
+
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
| 27 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
| 28 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
| 29 |
+
*.tar filter=lfs diff=lfs merge=lfs -text
|
| 30 |
+
*.tflite filter=lfs diff=lfs merge=lfs -text
|
| 31 |
+
*.tgz filter=lfs diff=lfs merge=lfs -text
|
| 32 |
+
*.wasm filter=lfs diff=lfs merge=lfs -text
|
| 33 |
+
*.xz filter=lfs diff=lfs merge=lfs -text
|
| 34 |
+
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 35 |
+
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
# Audio files - uncompressed
|
| 38 |
+
*.pcm filter=lfs diff=lfs merge=lfs -text
|
| 39 |
+
*.sam filter=lfs diff=lfs merge=lfs -text
|
| 40 |
+
*.raw filter=lfs diff=lfs merge=lfs -text
|
| 41 |
+
# Audio files - compressed
|
| 42 |
+
*.aac filter=lfs diff=lfs merge=lfs -text
|
| 43 |
+
*.flac filter=lfs diff=lfs merge=lfs -text
|
| 44 |
+
*.mp3 filter=lfs diff=lfs merge=lfs -text
|
| 45 |
+
*.ogg filter=lfs diff=lfs merge=lfs -text
|
| 46 |
+
*.wav filter=lfs diff=lfs merge=lfs -text
|
| 47 |
+
# Image files - uncompressed
|
| 48 |
+
*.bmp filter=lfs diff=lfs merge=lfs -text
|
| 49 |
+
*.gif filter=lfs diff=lfs merge=lfs -text
|
| 50 |
+
*.png filter=lfs diff=lfs merge=lfs -text
|
| 51 |
+
*.tiff filter=lfs diff=lfs merge=lfs -text
|
| 52 |
+
# Image files - compressed
|
| 53 |
+
*.jpg filter=lfs diff=lfs merge=lfs -text
|
| 54 |
+
*.jpeg filter=lfs diff=lfs merge=lfs -text
|
| 55 |
+
*.webp filter=lfs diff=lfs merge=lfs -text
|
allenai__WildChat-1M/LICENSE.md
ADDED
|
@@ -0,0 +1,428 @@
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|
|
| 1 |
+
# ODC Attribution License (ODC-By)
|
| 2 |
+
|
| 3 |
+
### Preamble
|
| 4 |
+
|
| 5 |
+
The Open Data Commons Attribution License is a license agreement
|
| 6 |
+
intended to allow users to freely share, modify, and use this Database
|
| 7 |
+
subject only to the attribution requirements set out in Section 4.
|
| 8 |
+
|
| 9 |
+
Databases can contain a wide variety of types of content (images,
|
| 10 |
+
audiovisual material, and sounds all in the same database, for example),
|
| 11 |
+
and so this license only governs the rights over the Database, and not
|
| 12 |
+
the contents of the Database individually. Licensors may therefore wish
|
| 13 |
+
to use this license together with another license for the contents.
|
| 14 |
+
|
| 15 |
+
Sometimes the contents of a database, or the database itself, can be
|
| 16 |
+
covered by other rights not addressed here (such as private contracts,
|
| 17 |
+
trademark over the name, or privacy rights / data protection rights
|
| 18 |
+
over information in the contents), and so you are advised that you may
|
| 19 |
+
have to consult other documents or clear other rights before doing
|
| 20 |
+
activities not covered by this License.
|
| 21 |
+
|
| 22 |
+
------
|
| 23 |
+
|
| 24 |
+
The Licensor (as defined below)
|
| 25 |
+
|
| 26 |
+
and
|
| 27 |
+
|
| 28 |
+
You (as defined below)
|
| 29 |
+
|
| 30 |
+
agree as follows:
|
| 31 |
+
|
| 32 |
+
### 1.0 Definitions of Capitalised Words
|
| 33 |
+
|
| 34 |
+
"Collective Database" - Means this Database in unmodified form as part
|
| 35 |
+
of a collection of independent databases in themselves that together are
|
| 36 |
+
assembled into a collective whole. A work that constitutes a Collective
|
| 37 |
+
Database will not be considered a Derivative Database.
|
| 38 |
+
|
| 39 |
+
"Convey" - As a verb, means Using the Database, a Derivative Database,
|
| 40 |
+
or the Database as part of a Collective Database in any way that enables
|
| 41 |
+
a Person to make or receive copies of the Database or a Derivative
|
| 42 |
+
Database. Conveying does not include interaction with a user through a
|
| 43 |
+
computer network, or creating and Using a Produced Work, where no
|
| 44 |
+
transfer of a copy of the Database or a Derivative Database occurs.
|
| 45 |
+
|
| 46 |
+
"Contents" - The contents of this Database, which includes the
|
| 47 |
+
information, independent works, or other material collected into the
|
| 48 |
+
Database. For example, the contents of the Database could be factual
|
| 49 |
+
data or works such as images, audiovisual material, text, or sounds.
|
| 50 |
+
|
| 51 |
+
"Database" - A collection of material (the Contents) arranged in a
|
| 52 |
+
systematic or methodical way and individually accessible by electronic
|
| 53 |
+
or other means offered under the terms of this License.
|
| 54 |
+
|
| 55 |
+
"Database Directive" - Means Directive 96/9/EC of the European
|
| 56 |
+
Parliament and of the Council of 11 March 1996 on the legal protection
|
| 57 |
+
of databases, as amended or succeeded.
|
| 58 |
+
|
| 59 |
+
"Database Right" - Means rights resulting from the Chapter III ("sui
|
| 60 |
+
generis") rights in the Database Directive (as amended and as transposed
|
| 61 |
+
by member states), which includes the Extraction and Re-utilisation of
|
| 62 |
+
the whole or a Substantial part of the Contents, as well as any similar
|
| 63 |
+
rights available in the relevant jurisdiction under Section 10.4.
|
| 64 |
+
|
| 65 |
+
"Derivative Database" - Means a database based upon the Database, and
|
| 66 |
+
includes any translation, adaptation, arrangement, modification, or any
|
| 67 |
+
other alteration of the Database or of a Substantial part of the
|
| 68 |
+
Contents. This includes, but is not limited to, Extracting or
|
| 69 |
+
Re-utilising the whole or a Substantial part of the Contents in a new
|
| 70 |
+
Database.
|
| 71 |
+
|
| 72 |
+
"Extraction" - Means the permanent or temporary transfer of all or a
|
| 73 |
+
Substantial part of the Contents to another medium by any means or in
|
| 74 |
+
any form.
|
| 75 |
+
|
| 76 |
+
"License" - Means this license agreement and is both a license of rights
|
| 77 |
+
such as copyright and Database Rights and an agreement in contract.
|
| 78 |
+
|
| 79 |
+
"Licensor" - Means the Person that offers the Database under the terms
|
| 80 |
+
of this License.
|
| 81 |
+
|
| 82 |
+
"Person" - Means a natural or legal person or a body of persons
|
| 83 |
+
corporate or incorporate.
|
| 84 |
+
|
| 85 |
+
"Produced Work" - a work (such as an image, audiovisual material, text,
|
| 86 |
+
or sounds) resulting from using the whole or a Substantial part of the
|
| 87 |
+
Contents (via a search or other query) from this Database, a Derivative
|
| 88 |
+
Database, or this Database as part of a Collective Database.
|
| 89 |
+
|
| 90 |
+
"Publicly" - means to Persons other than You or under Your control by
|
| 91 |
+
either more than 50% ownership or by the power to direct their
|
| 92 |
+
activities (such as contracting with an independent consultant).
|
| 93 |
+
|
| 94 |
+
"Re-utilisation" - means any form of making available to the public all
|
| 95 |
+
or a Substantial part of the Contents by the distribution of copies, by
|
| 96 |
+
renting, by online or other forms of transmission.
|
| 97 |
+
|
| 98 |
+
"Substantial" - Means substantial in terms of quantity or quality or a
|
| 99 |
+
combination of both. The repeated and systematic Extraction or
|
| 100 |
+
Re-utilisation of insubstantial parts of the Contents may amount to the
|
| 101 |
+
Extraction or Re-utilisation of a Substantial part of the Contents.
|
| 102 |
+
|
| 103 |
+
"Use" - As a verb, means doing any act that is restricted by copyright
|
| 104 |
+
or Database Rights whether in the original medium or any other; and
|
| 105 |
+
includes without limitation distributing, copying, publicly performing,
|
| 106 |
+
publicly displaying, and preparing derivative works of the Database, as
|
| 107 |
+
well as modifying the Database as may be technically necessary to use it
|
| 108 |
+
in a different mode or format.
|
| 109 |
+
|
| 110 |
+
"You" - Means a Person exercising rights under this License who has not
|
| 111 |
+
previously violated the terms of this License with respect to the
|
| 112 |
+
Database, or who has received express permission from the Licensor to
|
| 113 |
+
exercise rights under this License despite a previous violation.
|
| 114 |
+
|
| 115 |
+
Words in the singular include the plural and vice versa.
|
| 116 |
+
|
| 117 |
+
### 2.0 What this License covers
|
| 118 |
+
|
| 119 |
+
2.1. Legal effect of this document. This License is:
|
| 120 |
+
|
| 121 |
+
a. A license of applicable copyright and neighbouring rights;
|
| 122 |
+
|
| 123 |
+
b. A license of the Database Right; and
|
| 124 |
+
|
| 125 |
+
c. An agreement in contract between You and the Licensor.
|
| 126 |
+
|
| 127 |
+
2.2 Legal rights covered. This License covers the legal rights in the
|
| 128 |
+
Database, including:
|
| 129 |
+
|
| 130 |
+
a. Copyright. Any copyright or neighbouring rights in the Database.
|
| 131 |
+
The copyright licensed includes any individual elements of the
|
| 132 |
+
Database, but does not cover the copyright over the Contents
|
| 133 |
+
independent of this Database. See Section 2.4 for details. Copyright
|
| 134 |
+
law varies between jurisdictions, but is likely to cover: the Database
|
| 135 |
+
model or schema, which is the structure, arrangement, and organisation
|
| 136 |
+
of the Database, and can also include the Database tables and table
|
| 137 |
+
indexes; the data entry and output sheets; and the Field names of
|
| 138 |
+
Contents stored in the Database;
|
| 139 |
+
|
| 140 |
+
b. Database Rights. Database Rights only extend to the Extraction and
|
| 141 |
+
Re-utilisation of the whole or a Substantial part of the Contents.
|
| 142 |
+
Database Rights can apply even when there is no copyright over the
|
| 143 |
+
Database. Database Rights can also apply when the Contents are removed
|
| 144 |
+
from the Database and are selected and arranged in a way that would
|
| 145 |
+
not infringe any applicable copyright; and
|
| 146 |
+
|
| 147 |
+
c. Contract. This is an agreement between You and the Licensor for
|
| 148 |
+
access to the Database. In return you agree to certain conditions of
|
| 149 |
+
use on this access as outlined in this License.
|
| 150 |
+
|
| 151 |
+
2.3 Rights not covered.
|
| 152 |
+
|
| 153 |
+
a. This License does not apply to computer programs used in the making
|
| 154 |
+
or operation of the Database;
|
| 155 |
+
|
| 156 |
+
b. This License does not cover any patents over the Contents or the
|
| 157 |
+
Database; and
|
| 158 |
+
|
| 159 |
+
c. This License does not cover any trademarks associated with the
|
| 160 |
+
Database.
|
| 161 |
+
|
| 162 |
+
2.4 Relationship to Contents in the Database. The individual items of
|
| 163 |
+
the Contents contained in this Database may be covered by other rights,
|
| 164 |
+
including copyright, patent, data protection, privacy, or personality
|
| 165 |
+
rights, and this License does not cover any rights (other than Database
|
| 166 |
+
Rights or in contract) in individual Contents contained in the Database.
|
| 167 |
+
For example, if used on a Database of images (the Contents), this
|
| 168 |
+
License would not apply to copyright over individual images, which could
|
| 169 |
+
have their own separate licenses, or one single license covering all of
|
| 170 |
+
the rights over the images.
|
| 171 |
+
|
| 172 |
+
### 3.0 Rights granted
|
| 173 |
+
|
| 174 |
+
3.1 Subject to the terms and conditions of this License, the Licensor
|
| 175 |
+
grants to You a worldwide, royalty-free, non-exclusive, terminable (but
|
| 176 |
+
only under Section 9) license to Use the Database for the duration of
|
| 177 |
+
any applicable copyright and Database Rights. These rights explicitly
|
| 178 |
+
include commercial use, and do not exclude any field of endeavour. To
|
| 179 |
+
the extent possible in the relevant jurisdiction, these rights may be
|
| 180 |
+
exercised in all media and formats whether now known or created in the
|
| 181 |
+
future.
|
| 182 |
+
|
| 183 |
+
The rights granted cover, for example:
|
| 184 |
+
|
| 185 |
+
a. Extraction and Re-utilisation of the whole or a Substantial part of
|
| 186 |
+
the Contents;
|
| 187 |
+
|
| 188 |
+
b. Creation of Derivative Databases;
|
| 189 |
+
|
| 190 |
+
c. Creation of Collective Databases;
|
| 191 |
+
|
| 192 |
+
d. Creation of temporary or permanent reproductions by any means and
|
| 193 |
+
in any form, in whole or in part, including of any Derivative
|
| 194 |
+
Databases or as a part of Collective Databases; and
|
| 195 |
+
|
| 196 |
+
e. Distribution, communication, display, lending, making available, or
|
| 197 |
+
performance to the public by any means and in any form, in whole or in
|
| 198 |
+
part, including of any Derivative Database or as a part of Collective
|
| 199 |
+
Databases.
|
| 200 |
+
|
| 201 |
+
3.2 Compulsory license schemes. For the avoidance of doubt:
|
| 202 |
+
|
| 203 |
+
a. Non-waivable compulsory license schemes. In those jurisdictions in
|
| 204 |
+
which the right to collect royalties through any statutory or
|
| 205 |
+
compulsory licensing scheme cannot be waived, the Licensor reserves
|
| 206 |
+
the exclusive right to collect such royalties for any exercise by You
|
| 207 |
+
of the rights granted under this License;
|
| 208 |
+
|
| 209 |
+
b. Waivable compulsory license schemes. In those jurisdictions in
|
| 210 |
+
which the right to collect royalties through any statutory or
|
| 211 |
+
compulsory licensing scheme can be waived, the Licensor waives the
|
| 212 |
+
exclusive right to collect such royalties for any exercise by You of
|
| 213 |
+
the rights granted under this License; and,
|
| 214 |
+
|
| 215 |
+
c. Voluntary license schemes. The Licensor waives the right to collect
|
| 216 |
+
royalties, whether individually or, in the event that the Licensor is
|
| 217 |
+
a member of a collecting society that administers voluntary licensing
|
| 218 |
+
schemes, via that society, from any exercise by You of the rights
|
| 219 |
+
granted under this License.
|
| 220 |
+
|
| 221 |
+
3.3 The right to release the Database under different terms, or to stop
|
| 222 |
+
distributing or making available the Database, is reserved. Note that
|
| 223 |
+
this Database may be multiple-licensed, and so You may have the choice
|
| 224 |
+
of using alternative licenses for this Database. Subject to Section
|
| 225 |
+
10.4, all other rights not expressly granted by Licensor are reserved.
|
| 226 |
+
|
| 227 |
+
### 4.0 Conditions of Use
|
| 228 |
+
|
| 229 |
+
4.1 The rights granted in Section 3 above are expressly made subject to
|
| 230 |
+
Your complying with the following conditions of use. These are important
|
| 231 |
+
conditions of this License, and if You fail to follow them, You will be
|
| 232 |
+
in material breach of its terms.
|
| 233 |
+
|
| 234 |
+
4.2 Notices. If You Publicly Convey this Database, any Derivative
|
| 235 |
+
Database, or the Database as part of a Collective Database, then You
|
| 236 |
+
must:
|
| 237 |
+
|
| 238 |
+
a. Do so only under the terms of this License;
|
| 239 |
+
|
| 240 |
+
b. Include a copy of this License or its Uniform Resource Identifier (URI)
|
| 241 |
+
with the Database or Derivative Database, including both in the
|
| 242 |
+
Database or Derivative Database and in any relevant documentation;
|
| 243 |
+
|
| 244 |
+
c. Keep intact any copyright or Database Right notices and notices
|
| 245 |
+
that refer to this License; and
|
| 246 |
+
|
| 247 |
+
d. If it is not possible to put the required notices in a particular
|
| 248 |
+
file due to its structure, then You must include the notices in a
|
| 249 |
+
location (such as a relevant directory) where users would be likely to
|
| 250 |
+
look for it.
|
| 251 |
+
|
| 252 |
+
4.3 Notice for using output (Contents). Creating and Using a Produced
|
| 253 |
+
Work does not require the notice in Section 4.2. However, if you
|
| 254 |
+
Publicly Use a Produced Work, You must include a notice associated with
|
| 255 |
+
the Produced Work reasonably calculated to make any Person that uses,
|
| 256 |
+
views, accesses, interacts with, or is otherwise exposed to the Produced
|
| 257 |
+
Work aware that Content was obtained from the Database, Derivative
|
| 258 |
+
Database, or the Database as part of a Collective Database, and that it
|
| 259 |
+
is available under this License.
|
| 260 |
+
|
| 261 |
+
a. Example notice. The following text will satisfy notice under
|
| 262 |
+
Section 4.3:
|
| 263 |
+
|
| 264 |
+
Contains information from DATABASE NAME which is made available
|
| 265 |
+
under the ODC Attribution License.
|
| 266 |
+
|
| 267 |
+
DATABASE NAME should be replaced with the name of the Database and a
|
| 268 |
+
hyperlink to the location of the Database. "ODC Attribution License"
|
| 269 |
+
should contain a hyperlink to the URI of the text of this License. If
|
| 270 |
+
hyperlinks are not possible, You should include the plain text of the
|
| 271 |
+
required URI's with the above notice.
|
| 272 |
+
|
| 273 |
+
4.4 Licensing of others. You may not sublicense the Database. Each time
|
| 274 |
+
You communicate the Database, the whole or Substantial part of the
|
| 275 |
+
Contents, or any Derivative Database to anyone else in any way, the
|
| 276 |
+
Licensor offers to the recipient a license to the Database on the same
|
| 277 |
+
terms and conditions as this License. You are not responsible for
|
| 278 |
+
enforcing compliance by third parties with this License, but You may
|
| 279 |
+
enforce any rights that You have over a Derivative Database. You are
|
| 280 |
+
solely responsible for any modifications of a Derivative Database made
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| 281 |
+
by You or another Person at Your direction. You may not impose any
|
| 282 |
+
further restrictions on the exercise of the rights granted or affirmed
|
| 283 |
+
under this License.
|
| 284 |
+
|
| 285 |
+
### 5.0 Moral rights
|
| 286 |
+
|
| 287 |
+
5.1 Moral rights. This section covers moral rights, including any rights
|
| 288 |
+
to be identified as the author of the Database or to object to treatment
|
| 289 |
+
that would otherwise prejudice the author's honour and reputation, or
|
| 290 |
+
any other derogatory treatment:
|
| 291 |
+
|
| 292 |
+
a. For jurisdictions allowing waiver of moral rights, Licensor waives
|
| 293 |
+
all moral rights that Licensor may have in the Database to the fullest
|
| 294 |
+
extent possible by the law of the relevant jurisdiction under Section
|
| 295 |
+
10.4;
|
| 296 |
+
|
| 297 |
+
b. If waiver of moral rights under Section 5.1 a in the relevant
|
| 298 |
+
jurisdiction is not possible, Licensor agrees not to assert any moral
|
| 299 |
+
rights over the Database and waives all claims in moral rights to the
|
| 300 |
+
fullest extent possible by the law of the relevant jurisdiction under
|
| 301 |
+
Section 10.4; and
|
| 302 |
+
|
| 303 |
+
c. For jurisdictions not allowing waiver or an agreement not to assert
|
| 304 |
+
moral rights under Section 5.1 a and b, the author may retain their
|
| 305 |
+
moral rights over certain aspects of the Database.
|
| 306 |
+
|
| 307 |
+
Please note that some jurisdictions do not allow for the waiver of moral
|
| 308 |
+
rights, and so moral rights may still subsist over the Database in some
|
| 309 |
+
jurisdictions.
|
| 310 |
+
|
| 311 |
+
### 6.0 Fair dealing, Database exceptions, and other rights not affected
|
| 312 |
+
|
| 313 |
+
6.1 This License does not affect any rights that You or anyone else may
|
| 314 |
+
independently have under any applicable law to make any use of this
|
| 315 |
+
Database, including without limitation:
|
| 316 |
+
|
| 317 |
+
a. Exceptions to the Database Right including: Extraction of Contents
|
| 318 |
+
from non-electronic Databases for private purposes, Extraction for
|
| 319 |
+
purposes of illustration for teaching or scientific research, and
|
| 320 |
+
Extraction or Re-utilisation for public security or an administrative
|
| 321 |
+
or judicial procedure.
|
| 322 |
+
|
| 323 |
+
b. Fair dealing, fair use, or any other legally recognised limitation
|
| 324 |
+
or exception to infringement of copyright or other applicable laws.
|
| 325 |
+
|
| 326 |
+
6.2 This License does not affect any rights of lawful users to Extract
|
| 327 |
+
and Re-utilise insubstantial parts of the Contents, evaluated
|
| 328 |
+
quantitatively or qualitatively, for any purposes whatsoever, including
|
| 329 |
+
creating a Derivative Database (subject to other rights over the
|
| 330 |
+
Contents, see Section 2.4). The repeated and systematic Extraction or
|
| 331 |
+
Re-utilisation of insubstantial parts of the Contents may however amount
|
| 332 |
+
to the Extraction or Re-utilisation of a Substantial part of the
|
| 333 |
+
Contents.
|
| 334 |
+
|
| 335 |
+
### 7.0 Warranties and Disclaimer
|
| 336 |
+
|
| 337 |
+
7.1 The Database is licensed by the Licensor "as is" and without any
|
| 338 |
+
warranty of any kind, either express, implied, or arising by statute,
|
| 339 |
+
custom, course of dealing, or trade usage. Licensor specifically
|
| 340 |
+
disclaims any and all implied warranties or conditions of title,
|
| 341 |
+
non-infringement, accuracy or completeness, the presence or absence of
|
| 342 |
+
errors, fitness for a particular purpose, merchantability, or otherwise.
|
| 343 |
+
Some jurisdictions do not allow the exclusion of implied warranties, so
|
| 344 |
+
this exclusion may not apply to You.
|
| 345 |
+
|
| 346 |
+
### 8.0 Limitation of liability
|
| 347 |
+
|
| 348 |
+
8.1 Subject to any liability that may not be excluded or limited by law,
|
| 349 |
+
the Licensor is not liable for, and expressly excludes, all liability
|
| 350 |
+
for loss or damage however and whenever caused to anyone by any use
|
| 351 |
+
under this License, whether by You or by anyone else, and whether caused
|
| 352 |
+
by any fault on the part of the Licensor or not. This exclusion of
|
| 353 |
+
liability includes, but is not limited to, any special, incidental,
|
| 354 |
+
consequential, punitive, or exemplary damages such as loss of revenue,
|
| 355 |
+
data, anticipated profits, and lost business. This exclusion applies
|
| 356 |
+
even if the Licensor has been advised of the possibility of such
|
| 357 |
+
damages.
|
| 358 |
+
|
| 359 |
+
8.2 If liability may not be excluded by law, it is limited to actual and
|
| 360 |
+
direct financial loss to the extent it is caused by proved negligence on
|
| 361 |
+
the part of the Licensor.
|
| 362 |
+
|
| 363 |
+
### 9.0 Termination of Your rights under this License
|
| 364 |
+
|
| 365 |
+
9.1 Any breach by You of the terms and conditions of this License
|
| 366 |
+
automatically terminates this License with immediate effect and without
|
| 367 |
+
notice to You. For the avoidance of doubt, Persons who have received the
|
| 368 |
+
Database, the whole or a Substantial part of the Contents, Derivative
|
| 369 |
+
Databases, or the Database as part of a Collective Database from You
|
| 370 |
+
under this License will not have their licenses terminated provided
|
| 371 |
+
their use is in full compliance with this License or a license granted
|
| 372 |
+
under Section 4.8 of this License. Sections 1, 2, 7, 8, 9 and 10 will
|
| 373 |
+
survive any termination of this License.
|
| 374 |
+
|
| 375 |
+
9.2 If You are not in breach of the terms of this License, the Licensor
|
| 376 |
+
will not terminate Your rights under it.
|
| 377 |
+
|
| 378 |
+
9.3 Unless terminated under Section 9.1, this License is granted to You
|
| 379 |
+
for the duration of applicable rights in the Database.
|
| 380 |
+
|
| 381 |
+
9.4 Reinstatement of rights. If you cease any breach of the terms and
|
| 382 |
+
conditions of this License, then your full rights under this License
|
| 383 |
+
will be reinstated:
|
| 384 |
+
|
| 385 |
+
a. Provisionally and subject to permanent termination until the 60th
|
| 386 |
+
day after cessation of breach;
|
| 387 |
+
|
| 388 |
+
b. Permanently on the 60th day after cessation of breach unless
|
| 389 |
+
otherwise reasonably notified by the Licensor; or
|
| 390 |
+
|
| 391 |
+
c. Permanently if reasonably notified by the Licensor of the
|
| 392 |
+
violation, this is the first time You have received notice of
|
| 393 |
+
violation of this License from the Licensor, and You cure the
|
| 394 |
+
violation prior to 30 days after your receipt of the notice.
|
| 395 |
+
|
| 396 |
+
9.5 Notwithstanding the above, Licensor reserves the right to release
|
| 397 |
+
the Database under different license terms or to stop distributing or
|
| 398 |
+
making available the Database. Releasing the Database under different
|
| 399 |
+
license terms or stopping the distribution of the Database will not
|
| 400 |
+
withdraw this License (or any other license that has been, or is
|
| 401 |
+
required to be, granted under the terms of this License), and this
|
| 402 |
+
License will continue in full force and effect unless terminated as
|
| 403 |
+
stated above.
|
| 404 |
+
|
| 405 |
+
### 10.0 General
|
| 406 |
+
|
| 407 |
+
10.1 If any provision of this License is held to be invalid or
|
| 408 |
+
unenforceable, that must not affect the validity or enforceability of
|
| 409 |
+
the remainder of the terms and conditions of this License and each
|
| 410 |
+
remaining provision of this License shall be valid and enforced to the
|
| 411 |
+
fullest extent permitted by law.
|
| 412 |
+
|
| 413 |
+
10.2 This License is the entire agreement between the parties with
|
| 414 |
+
respect to the rights granted here over the Database. It replaces any
|
| 415 |
+
earlier understandings, agreements or representations with respect to
|
| 416 |
+
the Database.
|
| 417 |
+
|
| 418 |
+
10.3 If You are in breach of the terms of this License, You will not be
|
| 419 |
+
entitled to rely on the terms of this License or to complain of any
|
| 420 |
+
breach by the Licensor.
|
| 421 |
+
|
| 422 |
+
10.4 Choice of law. This License takes effect in and will be governed by
|
| 423 |
+
the laws of the relevant jurisdiction in which the License terms are
|
| 424 |
+
sought to be enforced. If the standard suite of rights granted under
|
| 425 |
+
applicable copyright law and Database Rights in the relevant
|
| 426 |
+
jurisdiction includes additional rights not granted under this License,
|
| 427 |
+
these additional rights are granted in this License in order to meet the
|
| 428 |
+
terms of this License.
|
allenai__WildChat-1M/README.md
ADDED
|
@@ -0,0 +1,263 @@
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|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: odc-by
|
| 3 |
+
size_categories:
|
| 4 |
+
- 1M<n<10M
|
| 5 |
+
task_categories:
|
| 6 |
+
- text-generation
|
| 7 |
+
- question-answering
|
| 8 |
+
- text2text-generation
|
| 9 |
+
pretty_name: WildChat-1M
|
| 10 |
+
dataset_info:
|
| 11 |
+
features:
|
| 12 |
+
- name: conversation_hash
|
| 13 |
+
dtype: string
|
| 14 |
+
- name: model
|
| 15 |
+
dtype: string
|
| 16 |
+
- name: timestamp
|
| 17 |
+
dtype: timestamp[us, tz=UTC]
|
| 18 |
+
- name: conversation
|
| 19 |
+
list:
|
| 20 |
+
- name: content
|
| 21 |
+
dtype: string
|
| 22 |
+
- name: country
|
| 23 |
+
dtype: string
|
| 24 |
+
- name: hashed_ip
|
| 25 |
+
dtype: string
|
| 26 |
+
- name: header
|
| 27 |
+
struct:
|
| 28 |
+
- name: accept-language
|
| 29 |
+
dtype: string
|
| 30 |
+
- name: user-agent
|
| 31 |
+
dtype: string
|
| 32 |
+
- name: language
|
| 33 |
+
dtype: string
|
| 34 |
+
- name: redacted
|
| 35 |
+
dtype: bool
|
| 36 |
+
- name: role
|
| 37 |
+
dtype: string
|
| 38 |
+
- name: state
|
| 39 |
+
dtype: string
|
| 40 |
+
- name: timestamp
|
| 41 |
+
dtype: timestamp[us, tz=UTC]
|
| 42 |
+
- name: toxic
|
| 43 |
+
dtype: bool
|
| 44 |
+
- name: turn_identifier
|
| 45 |
+
dtype: int64
|
| 46 |
+
- name: turn
|
| 47 |
+
dtype: int64
|
| 48 |
+
- name: language
|
| 49 |
+
dtype: string
|
| 50 |
+
- name: openai_moderation
|
| 51 |
+
list:
|
| 52 |
+
- name: categories
|
| 53 |
+
struct:
|
| 54 |
+
- name: harassment
|
| 55 |
+
dtype: bool
|
| 56 |
+
- name: harassment/threatening
|
| 57 |
+
dtype: bool
|
| 58 |
+
- name: harassment_threatening
|
| 59 |
+
dtype: bool
|
| 60 |
+
- name: hate
|
| 61 |
+
dtype: bool
|
| 62 |
+
- name: hate/threatening
|
| 63 |
+
dtype: bool
|
| 64 |
+
- name: hate_threatening
|
| 65 |
+
dtype: bool
|
| 66 |
+
- name: self-harm
|
| 67 |
+
dtype: bool
|
| 68 |
+
- name: self-harm/instructions
|
| 69 |
+
dtype: bool
|
| 70 |
+
- name: self-harm/intent
|
| 71 |
+
dtype: bool
|
| 72 |
+
- name: self_harm
|
| 73 |
+
dtype: bool
|
| 74 |
+
- name: self_harm_instructions
|
| 75 |
+
dtype: bool
|
| 76 |
+
- name: self_harm_intent
|
| 77 |
+
dtype: bool
|
| 78 |
+
- name: sexual
|
| 79 |
+
dtype: bool
|
| 80 |
+
- name: sexual/minors
|
| 81 |
+
dtype: bool
|
| 82 |
+
- name: sexual_minors
|
| 83 |
+
dtype: bool
|
| 84 |
+
- name: violence
|
| 85 |
+
dtype: bool
|
| 86 |
+
- name: violence/graphic
|
| 87 |
+
dtype: bool
|
| 88 |
+
- name: violence_graphic
|
| 89 |
+
dtype: bool
|
| 90 |
+
- name: category_scores
|
| 91 |
+
struct:
|
| 92 |
+
- name: harassment
|
| 93 |
+
dtype: float64
|
| 94 |
+
- name: harassment/threatening
|
| 95 |
+
dtype: float64
|
| 96 |
+
- name: harassment_threatening
|
| 97 |
+
dtype: float64
|
| 98 |
+
- name: hate
|
| 99 |
+
dtype: float64
|
| 100 |
+
- name: hate/threatening
|
| 101 |
+
dtype: float64
|
| 102 |
+
- name: hate_threatening
|
| 103 |
+
dtype: float64
|
| 104 |
+
- name: self-harm
|
| 105 |
+
dtype: float64
|
| 106 |
+
- name: self-harm/instructions
|
| 107 |
+
dtype: float64
|
| 108 |
+
- name: self-harm/intent
|
| 109 |
+
dtype: float64
|
| 110 |
+
- name: self_harm
|
| 111 |
+
dtype: float64
|
| 112 |
+
- name: self_harm_instructions
|
| 113 |
+
dtype: float64
|
| 114 |
+
- name: self_harm_intent
|
| 115 |
+
dtype: float64
|
| 116 |
+
- name: sexual
|
| 117 |
+
dtype: float64
|
| 118 |
+
- name: sexual/minors
|
| 119 |
+
dtype: float64
|
| 120 |
+
- name: sexual_minors
|
| 121 |
+
dtype: float64
|
| 122 |
+
- name: violence
|
| 123 |
+
dtype: float64
|
| 124 |
+
- name: violence/graphic
|
| 125 |
+
dtype: float64
|
| 126 |
+
- name: violence_graphic
|
| 127 |
+
dtype: float64
|
| 128 |
+
- name: flagged
|
| 129 |
+
dtype: bool
|
| 130 |
+
- name: detoxify_moderation
|
| 131 |
+
list:
|
| 132 |
+
- name: identity_attack
|
| 133 |
+
dtype: float64
|
| 134 |
+
- name: insult
|
| 135 |
+
dtype: float64
|
| 136 |
+
- name: obscene
|
| 137 |
+
dtype: float64
|
| 138 |
+
- name: severe_toxicity
|
| 139 |
+
dtype: float64
|
| 140 |
+
- name: sexual_explicit
|
| 141 |
+
dtype: float64
|
| 142 |
+
- name: threat
|
| 143 |
+
dtype: float64
|
| 144 |
+
- name: toxicity
|
| 145 |
+
dtype: float64
|
| 146 |
+
- name: toxic
|
| 147 |
+
dtype: bool
|
| 148 |
+
- name: redacted
|
| 149 |
+
dtype: bool
|
| 150 |
+
- name: state
|
| 151 |
+
dtype: string
|
| 152 |
+
- name: country
|
| 153 |
+
dtype: string
|
| 154 |
+
- name: hashed_ip
|
| 155 |
+
dtype: string
|
| 156 |
+
- name: header
|
| 157 |
+
struct:
|
| 158 |
+
- name: accept-language
|
| 159 |
+
dtype: string
|
| 160 |
+
- name: user-agent
|
| 161 |
+
dtype: string
|
| 162 |
+
splits:
|
| 163 |
+
- name: train
|
| 164 |
+
num_bytes: 6844366367.030628
|
| 165 |
+
num_examples: 837989
|
| 166 |
+
download_size: 3360836020
|
| 167 |
+
dataset_size: 6844366367.030628
|
| 168 |
+
configs:
|
| 169 |
+
- config_name: default
|
| 170 |
+
data_files:
|
| 171 |
+
- split: train
|
| 172 |
+
path: data/train-*
|
| 173 |
+
tags:
|
| 174 |
+
- instruction-finetuning
|
| 175 |
+
---
|
| 176 |
+
# Dataset Card for WildChat
|
| 177 |
+
|
| 178 |
+
## Dataset Description
|
| 179 |
+
|
| 180 |
+
- **Paper:** https://arxiv.org/abs/2405.01470
|
| 181 |
+
|
| 182 |
+
- **Interactive Search Tool:** https://wildvisualizer.com ([paper](https://arxiv.org/abs/2409.03753))
|
| 183 |
+
|
| 184 |
+
- **License:** [ODC-BY](https://opendatacommons.org/licenses/by/1-0/)
|
| 185 |
+
|
| 186 |
+
- **Language(s) (NLP):** multi-lingual
|
| 187 |
+
|
| 188 |
+
- **Point of Contact:** [Yuntian Deng](https://yuntiandeng.com/)
|
| 189 |
+
|
| 190 |
+
### Dataset Summary
|
| 191 |
+
|
| 192 |
+
WildChat is a collection of 1 million conversations between human users and ChatGPT, alongside demographic data, including state, country, hashed IP addresses, and request headers. We collected WildChat by offering online users free access to OpenAI's GPT-3.5 and GPT-4. In this version, 25.53% of the conversations come from the GPT-4 chatbot, while the rest come from the GPT-3.5 chatbot. The dataset contains a broad spectrum of user-chatbot interactions that are not previously covered by other instruction fine-tuning datasets: for example, interactions include ambiguous user requests, code-switching, topic-switching, political discussions, etc. WildChat can serve both as a dataset for instructional fine-tuning and as a valuable resource for studying user behaviors. Note that this version of the dataset only contains non-toxic user inputs/ChatGPT responses.
|
| 193 |
+
|
| 194 |
+
### Updates
|
| 195 |
+
|
| 196 |
+
**2024-10-17: Content Update.** Conversations flagged by [Niloofar Mireshghallah](https://homes.cs.washington.edu/~niloofar/) and her collaborators in ["Breaking News: Case Studies of Generative AI's Use in Journalism"](https://arxiv.org/abs/2406.13706) for containing PII or sensitive information have been removed from this version of the dataset.
|
| 197 |
+
|
| 198 |
+
**2024-07-22: Content Update.** All toxic conversations identified by the OpenAI Moderations API or Detoxify have been removed from this version of the dataset.
|
| 199 |
+
|
| 200 |
+
**2024-06-26: License Change.** We have updated the license of WildChat to [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). This change is retroactively applied to any previous downloads under the ImpACT license.
|
| 201 |
+
|
| 202 |
+
### Full Version with Toxic Content
|
| 203 |
+
|
| 204 |
+
For access to the full version of the WildChat dataset, which includes toxic conversations flagged by the OpenAI Moderations API or Detoxify, please refer to [WildChat-1M-Full](https://huggingface.co/datasets/allenai/WildChat-1M-Full). This version requires approval and justification for why toxic data is needed.
|
| 205 |
+
|
| 206 |
+
### Languages
|
| 207 |
+
|
| 208 |
+
68 languages were detected in WildChat.
|
| 209 |
+
|
| 210 |
+
### Personal and Sensitive Information
|
| 211 |
+
|
| 212 |
+
The data has been de-identified with Microsoft Presidio and hand-written rules by the authors.
|
| 213 |
+
|
| 214 |
+
### Data Fields
|
| 215 |
+
|
| 216 |
+
- `conversation_hash` (string): The hash of each conversation's content. This is not a unique key, as different conversations with the same content will share the same hash. For unique identifiers, use `turn_identifier` within each turn.
|
| 217 |
+
- `model` (string): The underlying OpenAI model, such as gpt-3.5-turbo or gpt-4.
|
| 218 |
+
- `timestamp` (timestamp): The timestamp of the last turn in the conversation in UTC.
|
| 219 |
+
- `conversation` (list): A list of user/assistant utterances. Each utterance is a dictionary containing the `role` of the speaker (user or assistant), the `content` of the utterance, the detected `language` of the utterance, whether the content of the utterance is considered `toxic`, and whether PII has been detected and anonymized (`redacted`). For user turns, there's also the hashed IP address `hashed_ip` of the turn, the state `state` and country `country` inferred from the original IP address, and the request headers `header` (which might be useful for linking multiple conversations from the same user when used in conjunction with `hashed_ip`). For assistant turns, there's a field `timestamp` which is the time when the backend server receives the full response from ChatGPT. For both user and assistant turns, there's a unique idenifier `turn_identifier`.
|
| 220 |
+
- `turn` (int): The number of turns in the conversation. A turn refers to one round of user-assistant interaction.
|
| 221 |
+
- `language` (string): The language of the conversation. Note that this is the most frequently detected language in the utterances of the conversation.
|
| 222 |
+
- `openai_moderation` (list): A list of OpenAI Moderation results. Each element in the list corresponds to one utterance in the conversation. When the content of an utterance is an empty string, the corresponding moderation reult is set to be an empty dictionary.
|
| 223 |
+
- `detoxify_moderation` (list): A list of Detoxify results. Each element in the list corresponds to one utterance in the conversation. When the content of an utterance is an empty string, the corresponding Detoxify reult is set to be an empty dictionary.
|
| 224 |
+
- `toxic` (bool): Whether this conversation contains any utterances considered to be toxic by either OpenAI Moderation or Detoxify.
|
| 225 |
+
- `redacted` (bool): Whether this conversation contains any utterances in which PII is detected and anonymized.
|
| 226 |
+
- `state` (string): The state inferred from the most common IP address in the conversation. Its value is sometimes `None` when GeoIP2 does not identify the state of an IP address.
|
| 227 |
+
- `country` (string): The country inferred from the most common IP address in the conversation. Its value is sometimes `None` when GeoIP2 does not identify the country of an IP address.
|
| 228 |
+
- `hashed_ip` (string): The most common hashed IP address in the conversation.
|
| 229 |
+
- `header` (string): The request header containing information about operating system, browser versions, and accepted languages. This field might be useful for linking multiple conversations from the same user when used in conjunction with `hashed_ip`. Note that every turn in a conversation has the same header, as this is the way we linked turns into conversations.
|
| 230 |
+
|
| 231 |
+
### Empty User Inputs
|
| 232 |
+
|
| 233 |
+
This dataset includes a small subset of conversations where users submitted empty inputs, sometimes leading to hallucinated responses from the assistant. This issue, first noticed by @yuchenlin, arises from the design of our Huggingface chatbot used for data collection, which did not restrict the submission of empty inputs. As a result, users could submit without entering any text, causing the assistant to generate responses without any user prompts. This occurs in a small fraction of the dataset.
|
| 234 |
+
|
| 235 |
+
### Licensing Information
|
| 236 |
+
|
| 237 |
+
WildChat is now made available under the [**ODC-BY License**](https://opendatacommons.org/licenses/by/1-0/). This change is retroactively applied to any previous downloads under the ImpACT license.
|
| 238 |
+
|
| 239 |
+
### Citation Information
|
| 240 |
+
|
| 241 |
+
Please consider citing [our paper](https://arxiv.org/abs/2405.01470) if you find this dataset useful:
|
| 242 |
+
```
|
| 243 |
+
@inproceedings{
|
| 244 |
+
zhao2024wildchat,
|
| 245 |
+
title={WildChat: 1M Chat{GPT} Interaction Logs in the Wild},
|
| 246 |
+
author={Wenting Zhao and Xiang Ren and Jack Hessel and Claire Cardie and Yejin Choi and Yuntian Deng},
|
| 247 |
+
booktitle={The Twelfth International Conference on Learning Representations},
|
| 248 |
+
year={2024},
|
| 249 |
+
url={https://openreview.net/forum?id=Bl8u7ZRlbM}
|
| 250 |
+
}
|
| 251 |
+
```
|
| 252 |
+
|
| 253 |
+
```
|
| 254 |
+
@misc{deng2024wildvisopensourcevisualizer,
|
| 255 |
+
title={WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild},
|
| 256 |
+
author={Yuntian Deng and Wenting Zhao and Jack Hessel and Xiang Ren and Claire Cardie and Yejin Choi},
|
| 257 |
+
year={2024},
|
| 258 |
+
eprint={2409.03753},
|
| 259 |
+
archivePrefix={arXiv},
|
| 260 |
+
primaryClass={cs.CL},
|
| 261 |
+
url={https://arxiv.org/abs/2409.03753},
|
| 262 |
+
}
|
| 263 |
+
```
|
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