llama2 code interprerter icon

# Llama2 Code Interpreter

🤗 CodeLlama 7B Finetuned Model (HF)

[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/release/python-390/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) This project allows LLM to generate code, execute it, receive feedback, debug, and answer questions based on the whole process. It is designed to be intuitive and versatile, capable of dealing with multiple languages and frameworks. [The purpose and direction of the project](https://github.com/SeungyounShin/Llama2-Code-Interpreter/wiki) ## Quick Start **Run the Gradio App**: ```bash python3 chatbot.py --path Seungyoun/codellama-7b-instruct-pad ``` ## News - 🔥🔥🔥[2023/08/27] We're thrilled to announce that our **[🤗 Llama2 Code Interpreter-7B](https://huggingface.co/Seungyoun/codellama-7b-instruct-pad) (Finetuned from [CodeLlama-7B-Instruct](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf))** model achieved a remarkable **70.12pass@1** on the [HumanEval Benchmarks](https://github.com/openai/human-eval). **HumanEval** | Model | Score(pass@1) | |-------------------------------|--------| | Codellama instruct 7b | 34.8% | | Codellama instruct 7b - finetuning | 70.12% | **GSM8K** | Model | Score | |-------------------------------|--------| | Code Llama 7B | 13% | | Code Llama 13B | 20.8% | | Codellama instruct 7b - finetuning | 28% | ## 🌟 Key Features - [x] 🚀 **Code Generation and Execution**: Llama2 is capable of generating code, which it then automatically identifies and executes within its generated code blocks. - [x] Monitors and retains Python variables that were used in previously executed code blocks. - [x] 🌟 At the moment, my focus is on "Data development for GPT-4 code interpretation" and "Enhancing the model using this data". For more details, check out the [feat/finetuning branch](https://github.com/SeungyounShin/Llama2-Code-Interpreter/tree/feat/finetuning) in our repository. - [x] 🌟 CodeLlama Support [CodeLlama2](https://github.com/facebookresearch/codellama) ## Examples ---
***Llama2 in Action***

example1_president_search_with_code

In the GIF, Llama2 is seen in action. A user types in the request: `Plot Nvidia 90 days chart.` Llama2, an advanced code interpreter fine-tuned on a select dataset, swiftly queries `Yahoo Finance`. Moments later, it fetches the latest Nvidia stock prices from the past 90 days. Using `Matplotlib`, Llama2 then generates a clear and detailed stock price chart for Nvidia, showcasing its performance over the given period. ## Installation 1. **Clone the Repository (if you haven't already)**: ```bash git clone https://github.com/SeungyounShin/Llama2-Code-Interpreter.git cd Llama2-Code-Interpreter ``` 2. **Install the required dependencies:** ```bash pip install -r requirements.txt ``` --- ### Run App with GPT4 finetunned Llama Model To start interacting with Llama2 via the Gradio UI using `codellama-7b-instruct-pad`, follow the steps below: 2. **Run the Gradio App**: ```bash python3 chatbot.py --path Seungyoun/codellama-7b-instruct-pad ``` For those who want to use other models: ### General Instructions to Run App To start interacting with Llama2 via the Gradio UI using other models: 1. **Run the Command**: ```bash python3 chatbot.py --model_path ``` Replace `` with the path to the model file you wish to use. A recommended model for chat interactions is `meta-llama/Llama-2-13b-chat`. ## Contributions Contributions, issues, and feature requests are welcome! Feel free to check [issues page](https://github.com/SeungyounShin/Llama2-Code-Interpreter/issues). ## License Distributed under the MIT License. See `LICENSE` for more information. ## Contact Seungyoun, Shin - 2022021568@korea.ac.kr ## Acknowledgement Here are some relevant and related projects that have contributed to the development of this work: 1. **llama2** : [GitHub Repository](https://github.com/facebookresearch/llama) 2. **yet-another-gpt-tutorial** : [GitHub Repository](https://github.com/sjchoi86/yet-another-gpt-tutorial/tree/main) These projects have been instrumental in providing valuable insights and resources, and their contributions are highly appreciated. ---