Text Generation
Transformers
PyTorch
English
llama
code
Eval Results (legacy)
text-generation-inference
Instructions to use pipizhao/Pandalyst-7B-V1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pipizhao/Pandalyst-7B-V1.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pipizhao/Pandalyst-7B-V1.1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("pipizhao/Pandalyst-7B-V1.1") model = AutoModelForCausalLM.from_pretrained("pipizhao/Pandalyst-7B-V1.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pipizhao/Pandalyst-7B-V1.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pipizhao/Pandalyst-7B-V1.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pipizhao/Pandalyst-7B-V1.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pipizhao/Pandalyst-7B-V1.1
- SGLang
How to use pipizhao/Pandalyst-7B-V1.1 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "pipizhao/Pandalyst-7B-V1.1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pipizhao/Pandalyst-7B-V1.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "pipizhao/Pandalyst-7B-V1.1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pipizhao/Pandalyst-7B-V1.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pipizhao/Pandalyst-7B-V1.1 with Docker Model Runner:
docker model run hf.co/pipizhao/Pandalyst-7B-V1.1
File size: 2,766 Bytes
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license: llama2
library_name: transformers
tags:
- code
model-index:
- name: Pandalyst-7B-V1.1
results:
- task:
type: text-generation
metrics:
- name: acc@1
type: acc@1
value: 0.0
verified: false
language:
- en
---
## Pandalyst: A large language model for mastering data analysis using pandas
<p align="center">
<img src="https://raw.githubusercontent.com/pipizhaoa/Pandalyst/master/imgs/pandalyst.png" width="300"/>
</p>
<p align="center">
🐱 <a href="https://github.com/pipizhaoa/Pandalyst" target="_blank">Github Repo</a> <br>
</p>
**What is Pandalyst**
- Pandalyst is a general large language model specifically trained to process and analyze data using the pandas library.
**How is Pandalyst**
- Pandalyst has strong generalization capabilities for data tables in different fields and different data analysis needs.
**Why is Pandalyst**
- Pandalyst is open source and free to use, and its small parameter size (7B/13B) allows us to easily deploy it on local PC.
- Pandalyst can handle complex data tables (multiple columns and multiple rows), allowing us to enter enough context to describe our table in detail.
- Pandalyst has very competitive performance, significantly outperforming models of the same size and even outperforming some of the strongest closed-source models.
## News
- 🔥[2023/10/15] Now we can **plot** 📈! and much more powerful! We released **Pandalyst-7B-V1.2**, which was trained on **CodeLlama-7b-Python** and it surpasses **ChatGPT-3.5 (2023/06/13)**, **Pandalyst-7B-V1.1** and **WizardCoder-Python-13B-V1.0** in our **PandaTest_V1.0**.
- 🤖️[2023/09/30] We released **Pandalyst-7B-V1.1** , which was trained on **CodeLlama-7b-Python** and achieves the **76.1 exec@1** in our **PandaTest_V1.0** and surpasses **WizardCoder-Python-13B-V1.0** and **ChatGPT-3.5 (2023/06/13)**.
| Model | Checkpoint | Support plot | License |
|---------------------|--------------------------------------------------------------------------------------------|--------------| ----- |
| 🔥Pandalyst-7B-V1.2 | 🤗 <a href="https://huggingface.co/pipizhao/Pandalyst-7B-V1.2" target="_blank">HF Link</a> | ✅ | <a href="https://ai.meta.com/resources/models-and-libraries/llama-downloads/" target="_blank">Llama2</a> |
| Pandalyst-7B-V1.1 | 🤗 <a href="https://huggingface.co/pipizhao/Pandalyst-7B-V1.1" target="_blank">HF Link</a> | ❌ | <a href="https://ai.meta.com/resources/models-and-libraries/llama-downloads/" target="_blank">Llama2</a> |
## Usage and Human evaluation
Please refer to <a href="https://github.com/pipizhaoa/Pandalyst" target="_blank">Github</a>. |