https://github.com/vhidvz/question-answering
Q/A microservice powered by a GPT-2 model, expertly fine-tuned for Persian-language contexts
https://github.com/vhidvz/question-answering
ai fastapi gpt-2 haystack huggingface persian-nlp question-answering
Last synced: 11 months ago
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Q/A microservice powered by a GPT-2 model, expertly fine-tuned for Persian-language contexts
- Host: GitHub
- URL: https://github.com/vhidvz/question-answering
- Owner: vhidvz
- License: mit
- Created: 2024-09-09T08:45:07.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-05T00:03:05.000Z (11 months ago)
- Last Synced: 2025-03-05T01:18:45.549Z (11 months ago)
- Topics: ai, fastapi, gpt-2, haystack, huggingface, persian-nlp, question-answering
- Language: Python
- Homepage: https://vhidvz.github.io/question-answering/
- Size: 86.9 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Quick Start
Q/A microservice powered by a GPT-2 model, expertly fine-tuned for Persian-language contexts. This solution delivers accurate, context-aware responses, tailored specifically to the nuances of Persian dialogue and communication.
```sh
git clone git@github.com:vhidvz/question-answering.git
cd question-answering && docker-compose up -d
```
**Docker Hub:**
```sh
docker run -p 8000:8000 vhidvz/question-answering:latest
```
Endpoints are fully documented using OpenAPI Specification 3 (OAS3) at:
- ReDoc:
- Swagger:
> Note: To enable in-memory document storage, simply remove the `ELASTICSEARCH_*` environment variables.
## Documentation
To generate the documentation for the python model, execute the following command:
```sh
pdoc --output-dir docs model.py
```