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# Dash + Hugging Face Demo | |
This is a demo application showcasing how to use Dash with Hugging Face models deployed on Hugging Face Spaces using Docker. | |
## Features | |
- **Sentiment Analysis**: Analyze the sentiment of text using a pre-trained model | |
- **Text Generation**: Generate text based on prompts using GPT-2 | |
- **Interactive Visualizations**: View sentiment analysis results with Plotly charts | |
- **Responsive Design**: Bootstrap-based UI that works on all devices | |
## Models Used | |
- Sentiment Analysis: `cardiffnlp/twitter-roberta-base-sentiment-latest` | |
- Text Generation: `gpt2` | |
## Local Development | |
1. Clone this repository | |
2. Install dependencies: `pip install -r requirements.txt` | |
3. Run the app: `python app.py` | |
4. Open your browser to `http://localhost:7860` | |
## Deployment on Hugging Face Spaces | |
This app is configured to run on Hugging Face Spaces using Docker: | |
1. The Dockerfile sets up the Python environment | |
2. Port 7860 is exposed (required by HF Spaces) | |
3. Models are loaded automatically when the container starts | |
## File Structure | |
``` | |
βββ app.py # Main Dash application | |
βββ requirements.txt # Python dependencies | |
βββ Dockerfile # Docker configuration | |
βββ README.md # This file | |
``` | |
## Configuration | |
The app automatically detects when running on Hugging Face Spaces and configures itself accordingly. No additional setup is required. |