https://github.com/hk669/language-detection-model
This model detects which language is given by the user.
https://github.com/hk669/language-detection-model
docker fastapi language-model languagedetection machine-learning
Last synced: about 2 months ago
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This model detects which language is given by the user.
- Host: GitHub
- URL: https://github.com/hk669/language-detection-model
- Owner: Hk669
- License: mit
- Created: 2023-07-09T13:02:08.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-07-14T16:10:20.000Z (almost 3 years ago)
- Last Synced: 2025-01-23T06:32:34.463Z (over 1 year ago)
- Topics: docker, fastapi, language-model, languagedetection, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 955 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Language Detection Model
This repository contains code for a language detection model based on machine learning. The model is built using scikit-learn and deployed as a FastAPI web application using Docker.
## Features
- Predicts the language of a given text using a pre-trained language detection model.
- Supports multiple languages including Arabic, Danish, Dutch, English, French, German, Greek, Hindi, Italian, Kannada, Malayalam, Portuguese, Russian, Spanish, Swedish, Tamil, and Turkish.
- Provides a user-friendly API interface for making predictions.
## Setup and Installation
To run the language detection model locally, follow these steps:
1. Clone this repository: `git clone https://github.com/Hk669/language-detection-model.git`
2. Install Docker on your machine: https://docs.docker.com/get-docker/
3. Build the Docker image: `docker build -t language-detection-app .`
4. Run the Docker container: `docker run -p 80:80 language-detection-app`
5. Access the API at `http://localhost:80` or `http://127.0.0.1:80`
## API Usage
Make a POST request to the `/predict` endpoint with the following JSON payload:
## Contributing
Contributions are welcome! If you find any issues or have suggestions for improvement, please open an issue or submit a pull request.
## License
This project is licensed under the MIT License.