InstaMatch is a cloud instance matching tool for machine learning models. It fetches model information from HuggingFace and recommends suitable cloud instances from AWS, Azure, and GCP based on the model's requirements.
- Fetch model information from HuggingFace API
- Estimate model requirements (vCPUs and memory)
- Recommend suitable cloud instances from AWS, Azure, and GCP
- Display primary and backup recommendations
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Clone the repository: ```sh git clone https://github.com/yourusername/InstaMatch.git cd InstaMatch ```
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Create and activate a virtual environment: ```sh python3 -m venv venv source venv/bin/activate ```
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Install the required dependencies: ```sh pip install -r requirements.txt ```
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Set up your HuggingFace API token in a `.env` file: ```sh echo "HUGGING_FACE_TOKEN=your_huggingface_token" > .env ```
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Run the application: ```sh python app.py ```
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Open the provided URL in your browser.
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Enter a model name from HuggingFace (e.g., `gpt2`, `bert-base-uncased`) and click "Get Recommendations".
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View the model requirements and cloud instance recommendations.
- `app.py`: Main application file
- `cloud_instances.csv`: CSV file containing cloud instance data
- `requirements.txt`: List of required Python packages
- `utils/`: Utility functions and modules
This project is licensed under the MIT License." > README.md
git add README.md git commit -m "Add README file"