Create DEPLOYMENT_GUIDE

DEPLOYMENT_GUIDE

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+# Deployment Guide for Voice Recognition Model on Hugging Face
+
+This guide explains how to deploy the enhanced voice recognition model using the provided files.
+
+## Prerequisites
+
+- Docker installed on your system
+- Hugging Face account
+- Hugging Face CLI installed (`pip install huggingface_hub`)
+- API token from Hugging Face
+
+## Files Included
+
+- `app.py`: FastAPI application serving the model
+- `requirements.txt`: Python dependencies
+- `Dockerfile`: Container configuration
+- `README.md`: Project overview and usage instructions
+
+## Steps to Deploy
+
+### 1. Build Docker Image
+
+```bash
+docker build -t voice-recognition-app .
+```
+
+### 2. Run Docker Container Locally
+
+```bash
+docker run -p 8000:8000 voice-recognition-app
+```
+
+The API will be available at `http://localhost:8000`.
+
+### 3. Test API Locally
+
+Use curl or any HTTP client to test the `/predict` endpoint:
+
+```bash
+curl -X POST "http://localhost:8000/predict" -F "file=@path_to_audio_file.wav"
+```
+
+### 4. Push to Hugging Face
+
+Login to Hugging Face CLI:
+
+```bash
+huggingface-cli login
+```
+
+Create a new repository on Hugging Face or use an existing one.
+
+Push your Docker image or code to Hugging Face Spaces or Model Hub as per your preference.
+
+### 5. Monitor and Manage
+
+Use the Hugging Face interface to monitor usage, logs, and manage your deployment.
+
+## Notes
+
+- Ensure your model file `voice_recognition_final_enhanced.pth` is included in the deployment package or accessible by the app.
+- Adjust the `app.py` if you change the model path or architecture.
+- For GPU support, configure your Docker environment accordingly.
+
+## References
+
+- [FastAPI Documentation](https://fastapi.tiangolo.com/)
+- [Hugging Face Spaces](https://huggingface.co/spaces)
+- [Docker Documentation](https://docs.docker.com/)