| license: cc-by-nc-nd-4.0 | |
| datasets: | |
| - ajibawa-2023/Python-Code-23k-ShareGPT | |
| language: | |
| - en | |
| tags: | |
| - code | |
| **Python-Code-33B** | |
| Large Language Models (LLMs) are good with code generations. Sometimes LLMs do make mistakes in code generation. How about if they can give detailed explanation along with the code. | |
| This is what I have tried over here. The base Llama-2 model was used for training purpose. It is trained on around 23000+ set of codes. Each set having 2 conversations. | |
| This data was generated using GPT-3.5, GPT-4 etc. This conversation is in Vicuna/ShareGPT format. Each set, along with code, has detailed explanation. | |
| I have released the [data](https://huggingface.co/datasets/ajibawa-2023/Python-Code-23k-ShareGPT). | |
| **Training:** | |
| Entire dataset was trained on Azure 4 x A100 80GB. For 3 epoch, training took 42 hours. DeepSpeed codebase was used for training purpose. This was trained on Llama-1 by Meta. | |
| **GPTQ GGML & AWQ** | |
| GPTQ: [Link](https://huggingface.co/TheBloke/Python-Code-33B-GPTQ) | |
| GGUF: [Link](https://huggingface.co/TheBloke/Python-Code-33B-GGUF) | |
| AWQ: [Link](https://huggingface.co/TheBloke/Python-Code-33B-AWQ) | |
| **Example Prompt:** | |
| ``` | |
| This is a conversation with your helpful AI assistant. AI assistant can generate Python Code along with necessary explanation. | |
| Context | |
| You are a helpful AI assistant. | |
| USER: <prompt> | |
| ASSISTANT: | |
| ``` |