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--- |
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title: Code Generation with CodeT5 |
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emoji: 😻 |
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colorFrom: yellow |
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colorTo: green |
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sdk: gradio |
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sdk_version: 5.20.1 |
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app_file: app.py |
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pinned: false |
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license: mit |
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hf_oauth: true |
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hf_oauth_scopes: |
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- inference-api |
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short_description: ' This repository demonstrates how to leverage CodeT5-base' |
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--- |
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# 🚀 Code Generation with CodeT5 |
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Welcome to the **Code Generation with CodeT5** project! This repository demonstrates how to leverage the `Salesforce/codet5-base` model for generating Python code snippets based on textual prompts. The project utilizes Gradio for creating interactive web interfaces and is deployed on Hugging Face Spaces. |
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## 📚 Repository Contents |
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- **Model Configuration:** |
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Stored in `config.json`, this file defines the architecture and settings of the CodeT5 model. |
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- **Tokenizer Special Tokens:** |
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Located in `special_tokens_map.json`, it maps special tokens used during tokenization. |
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- **Training Hyperparameters:** |
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Found in `training_args.json`, this file contains parameters like learning rate, batch size, and number of epochs used during training. |
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- **Inference Code:** |
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The `app.py` script loads the model and provides an interface for code generation. |
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- **Dependencies:** |
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Listed in `requirements.txt`, these are the necessary packages for running the model. |
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- **Documentation:** |
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This `README.md` provides an overview and guide for setting up and using the repository. |
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## 🔧 Setup & Usage |
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### 1. Clone the Repository |
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Clone the repository to your local machine: |
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```bash |
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git clone https://github.com/your-username/codegen-model-repo.git |
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cd codegen-model-repo |
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``` |
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### 2. Install Dependencies |
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Install the required packages using pip: |
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```bash |
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pip install -r requirements.txt |
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``` |
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### 3. Run the Gradio App |
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Launch the Gradio app to start generating code: |
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```bash |
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streamlit run app.py |
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``` |
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Access the app in your browser to input prompts and receive generated code snippets. |
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## 🌐 Deploying on Hugging Face Spaces |
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To deploy your Gradio app on Hugging Face Spaces: |
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1. **Create a New Space:** |
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- Visit [Hugging Face Spaces](https://huggingface.co/spaces) and create a new Space. |
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- Select Gradio as the SDK. |
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2. **Push Your Code:** |
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- Initialize a Git repository in your project directory. |
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- Commit your code and push it to the new Space's repository. |
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For a detailed walkthrough on deploying Gradio apps to Hugging Face Spaces, refer to this [tutorial](https://pyimagesearch.com/2024/12/30/deploy-gradio-apps-on-hugging-face-spaces/). |
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## 📄 License |
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This project is licensed under the MIT License. |
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