Upload Qwen3 1.7B Nuosu translation LoRA research preview

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+checkpoint-100/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-102/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+- ii
+- zh
+- en
+license: apache-2.0
+library_name: peft
+pipeline_tag: text-generation
+base_model: Qwen/Qwen3-1.7B-Base
+base_model_relation: adapter
+datasets:
+- TianYeZ1214/NuosuBench
+- nanxidajun/NuosuBburma-OCR-Evaluation-Set
+tags:
+- qwen3
+- nuosu
+- standard-liangshan-yi
+- translation
+- peft
+- lora
+- research
+---
+
+# Qwen3-1.7B-Base Nuosu Translation LoRA
+
+This repository contains a research-preview LoRA adapter for translation
+between Standard Liangshan Yi (Nuosu), Chinese, and English. It is based on
+`Qwen/Qwen3-1.7B-Base` and is not a standalone model.
+
+本仓库发布的是面向凉山规范彝文（诺苏语）的研究预览版翻译 LoRA。它基于
+`Qwen/Qwen3-1.7B-Base`，必须与基础模型一起加载，不是完整模型，也不是通用对话模型。
+
+## Intended use / 适用范围
+
+- Chinese-to-Nuosu, Nuosu-to-Chinese, and English-related translation research.
+- Reproducible evaluation and continued corpus/model development.
+- Explicit translation instructions with deterministic decoding.
+
+该模型适合明确指定翻译方向的研究和实验。它没有经过足够的真实多轮对话训练，不适合作为
+通用聊天助手，也不应被用于需要专业母语翻译质量的场景。
+
+## Training data / 训练数据
+
+The adapter was trained through OCR-ground-truth continued pretraining,
+dictionary SFT, and short/long translation SFT. Sources used by this run:
+
+- [NuosuBench](https://huggingface.co/datasets/TianYeZ1214/NuosuBench)
+- [NuosuBburma OCR Evaluation Set](https://huggingface.co/datasets/nanxidajun/NuosuBburma-OCR-Evaluation-Set)
+- [Yi–Chinese Electronic Dictionary](https://www.yixueyanjiu.com/dict/)
+
+NuosuBench was split into fixed train, validation, and held-out research-test
+partitions. The held-out partition was not used for gradient training.
+
+## Evaluation / 评测
+
+Deterministic greedy decoding was used with `max_new_tokens=96`.
+
+| Split or target | Records | chrF2 | Exact match |
+|---|---:|---:|---:|
+| Validation, overall | 192 | 28.1479 | 0.00% |
+| Research test, overall | 11,171 | 38.5067 | 17.21% |
+| Research test, Nuosu target | 4,263 | 25.1546 | 2.77% |
+| Research test, Chinese target | 2,889 | 39.5248 | 13.46% |
+| Research test, English target | 811 | 50.0656 | 22.19% |
+
+The 192-row validation gate had no empty outputs or replacement characters and
+a 1.04% length-truncation rate. On the full research test, the empty-output
+rate was 0.009%, the replacement-character rate was 1.77%, and the
+length-truncation rate was 3.72%.
+
+Automatic scores do not establish linguistic correctness. Native-speaker
+review remains necessary.
+
+## Known limitations / 已知问题
+
+- Some difficult Chinese-to-Nuosu prompts trigger repetitive Yi syllable
+  loops until the generation limit.
+- A small number of truncated generations end with the Unicode replacement
+  character (`�`).
+- Rare expressions, culturally specific phrases, and long translations remain
+  unreliable.
+- The training distribution is translation-heavy. Open-ended writing and
+  multi-turn dialogue behavior are not reliable.
+- The model has not received comprehensive native-speaker evaluation.
+
+本模型最明显的问题是少量困难汉译彝输入会产生重复循环，直到达到生成长度上限。因此本版
+仅作为 research preview 发布，不应描述为成熟的彝语翻译系统。
+
+## Usage / 使用方法
+
+```python
+import torch
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+base_id = "Qwen/Qwen3-1.7B-Base"
+adapter_id = "NiceAsiv/Qwen3-1.7B-Base-Nuosu-LoRA"
+
+tokenizer = AutoTokenizer.from_pretrained(adapter_id)
+base = AutoModelForCausalLM.from_pretrained(
+    base_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+model = PeftModel.from_pretrained(base, adapter_id)
+model.eval()
+
+messages = [
+    {
+        "role": "user",
+        "content": "请把“欢迎来到凉山”翻译成凉山规范彝文，只输出译文。",
+    }
+]
+prompt = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True,
+)
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+stop_ids = sorted(
+    {
+        tokenizer.eos_token_id,
+        tokenizer.convert_tokens_to_ids("<|im_end|>"),
+        tokenizer.convert_tokens_to_ids("<|endoftext|>"),
+    }
+)
+
+with torch.inference_mode():
+    output = model.generate(
+        **inputs,
+        max_new_tokens=96,
+        do_sample=False,
+        eos_token_id=stop_ids,
+        pad_token_id=tokenizer.pad_token_id,
+    )
+
+print(
+    tokenizer.decode(
+        output[0, inputs["input_ids"].shape[-1]:],
+        skip_special_tokens=True,
+    )
+)
+```
+
+Use explicit translation instructions and deterministic decoding. Stop and
+discard an output if it enters a repetition loop.
+
+## Training summary
+
+- Base model: `Qwen/Qwen3-1.7B-Base`
+- Adapter: LoRA, rank 32, alpha 64, dropout 0.05
+- Precision: BF16
+- Training topology: three GPUs with distributed data parallelism
+- Stages: OCR CPT → dictionary SFT → short translation SFT → long translation SFT
+
+## Disclaimer / 免责声明
+
+This artifact is provided for academic and research use. Users are responsible
+for validating generated translations and reviewing the terms of each cited
+data source. Do not use generated text as authoritative linguistic,
+educational, legal, medical, or public-service translation without qualified
+human review.

adapter_config.json

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+  "base_model_name_or_path": "Qwen/Qwen3-1.7B-Base",
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+  "megatron_core": "megatron.core",
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+  "peft_type": "LORA",
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chat_template.jinja

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checkpoint-100/README.md

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+---
+base_model: /home/xjtuoss/nuosu-project/models/Qwen3-1.7B-Base-36be17a0
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:/home/xjtuoss/nuosu-project/models/Qwen3-1.7B-Base-36be17a0
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.18.1

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checkpoint-102/README.md

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+---
+base_model: /home/xjtuoss/nuosu-project/models/Qwen3-1.7B-Base-36be17a0
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:/home/xjtuoss/nuosu-project/models/Qwen3-1.7B-Base-36be17a0
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.18.1

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