feat: model card

README.md

@@ -4,4 +4,112 @@ datasets:
 - ise-uiuc/Magicoder-OSS-Instruct-75K
 library_name: transformers
 pipeline_tag: text-generation
----
+---
+# 🎩 Magicoder: Source Code Is All You Need
+
+> Refer to our GitHub repo [ise-uiuc/magicoder](https://github.com/ise-uiuc/magicoder/) for an up-to-date introduction to the Magicoder family!
+
+* 🎩**Magicoder** is a model family empowered by 🪄**OSS-Instruct**, a novel approach to enlightening LLMs with open-source code snippets for generating *low-bias* and *high-quality* instruction data for code.
+* 🪄**OSS-Instruct** mitigates the *inherent bias* of the LLM-synthesized instruction data by empowering them with *a wealth of open-source references* to produce more diverse, realistic, and controllable data.
+
+![Overview of OSS-Instruct](assets/overview.svg)
+![Overview of Result](assets/result.png)
+
+## Model Details
+
+### Model Description
+
+* **Developed by:**
+[Yuxiang Wei](https://yuxiang.cs.illinois.edu),
+[Zhe Wang](https://github.com/zhewang2001),
+[Jiawei Liu](https://jiawei-site.github.io),
+[Yifeng Ding](https://yifeng-ding.com),
+[Lingming Zhang](https://lingming.cs.illinois.edu)
+* **License:** [Llama 2](https://ai.meta.com/llama/license/)
+* **Finetuned from model:** [CodeLlama-7b-Python-hf](https://huggingface.co/codellama/CodeLlama-7b-Python-hf)
+
+### Model Sources
+
+* **Repository:** <https://github.com/ise-uiuc/magicoder>
+* **Paper:** <https://arxiv.org/pdf/2312.02120.pdf>
+* **Demo (powered by [Gradio](https://www.gradio.app)):**
+<https://github.com/ise-uiuc/magicoder/tree/main/demo>
+
+### Training Data
+
+* [Magicoder-OSS-Instruct-75K](https://huggingface.co/datasets/ise-uiuc/Magicoder_oss_instruct_75k): generated through **OSS-Instruct** using `gpt-3.5-turbo-1106` and used to train both Magicoder and Magicoder-S series.
+
+## Uses
+
+### Direct Use
+
+Magicoders are designed and best suited for **coding tasks**.
+
+### Out-of-Scope Use
+
+Magicoders may not work well in non-coding tasks.
+
+## Bias, Risks, and Limitations
+
+Magicoders may sometimes make errors, producing misleading contents, or struggle to manage tasks that are not related to coding.
+
+### Recommendations
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model. Make sure you installed the [transformers](https://huggingface.co/docs/transformers/index) library.
+
+```python
+from transformers import pipeline
+import torch
+
+MAGICODER_PROMPT = """You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.
+
+@@ Instruction
+{instruction}
+
+@@ Response
+"""
+
+instruction = <Your code instruction here>
+
+prompt = MAGICODER_PROMPT.format(instruction=instruction)
+generator = pipeline(
+    model="ise-uiuc/Magicoder-CL-7B",
+    task="text-generation",
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+result = generator(prompt, max_length=1024, num_return_sequences=1, temperature=0.0)
+print(result[0]["generated_text"])
+```
+
+## Technical Details
+
+Refer to our GitHub repo: [ise-uiuc/magicoder](https://github.com/ise-uiuc/magicoder/).
+
+## Citation
+
+```bibtex
+@misc{magicoder,
+    title={Magicoder: Source Code Is All You Need}, 
+    author={Yuxiang Wei and Zhe Wang and Jiawei Liu and Yifeng Ding and Lingming Zhang},
+    year={2023},
+    eprint={2312.02120},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+## Acknowledgements
+
+* [WizardCoder](https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder): Evol-Instruct
+* [DeepSeek-Coder](https://github.com/deepseek-ai/DeepSeek-Coder): Base model for Magicoder-DS
+* [CodeLlama](https://ai.meta.com/research/publications/code-llama-open-foundation-models-for-code/): Base model for Magicoder-CL
+* [StarCoder](https://arxiv.org/abs/2305.06161): Data decontamination
+
+## Important Note
+
+Magicoder models are trained on the synthetic data generated by OpenAI models. Please pay attention to OpenAI's [terms of use](https://openai.com/policies/terms-of-use) when using the models and the datasets. Magicoders will not compete with OpenAI's commercial products.