dnnsdunca's picture
Custom Mistral 7B model training project focused on code generation. This README assumes your project is hosted on a platform like GitHub, GitLab, or Bitbucket and provides a basic structure that you can customize further based on the specifics of your project, such as the datasets used, model architecture details, and any additional features or considerations. --- # Custom Mistral 7B Model for Code Generation Welcome to the Custom Mistral 7B Model Training for Code Generation project. This project aims to fine-tune the Mistral 7B model, a transformer-based neural network, to improve its performance in generating code across various programming languages including but not limited to JavaScript, HTML, CSS, Python, Kotlin, Swift, and Java. ## Project Overview The objective of this project is to create a more efficient and versatile code generation model by training on a diverse dataset. Our goal is to enhance the model's understanding of programming languages' syntax, semantics, and context. ## Getting Started ### Prerequisites - Python 3.8+ - PyTorch 1.8+ - Hugging Face Transformers - Access to a GPU (recommended for training) ### Installation Clone this repository to get started with the project. ```bash git clone https://yourrepositorylink.git cd your-project-name ``` Install the required dependencies: ```bash pip install -r requirements.txt ``` ### Dataset The training dataset comprises millions of lines of code across various languages, sourced from open-source projects, coding challenge solutions, and other educational resources. ### Training To start the training process, run the following command: ```bash python --model_name_or_path Mistral7B --train_data_file ./data/train_dataset.json --output_dir ./trained_model ``` Please refer to `` for additional configuration options. ## Usage After training, you can use the model to generate code snippets. Here's a quick example: ```python from transformers import pipeline generator = pipeline('text-generation', model='./trained_model') code = generator("Generate a Python function that reverses a string:", max_length=100)[0]['generated_text'] print(code) ``` ## Contributing Contributions to this project are welcome! Please refer to the `` file for more details on how to contribute. ## License This project is licensed under the MIT License - see the []( file for details. ## Acknowledgments - Thanks to the original authors and contributors of the Mistral 7B model. - Special thanks to all the contributors of the datasets used for training.
b301b0f verified