https://github.com/blaizzy/llmops
Deploy and scale Large Language Models (LLMs) in production.
https://github.com/blaizzy/llmops
Last synced: about 1 year ago
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Deploy and scale Large Language Models (LLMs) in production.
- Host: GitHub
- URL: https://github.com/blaizzy/llmops
- Owner: Blaizzy
- License: mit
- Created: 2023-11-19T19:25:31.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-20T11:34:50.000Z (almost 2 years ago)
- Last Synced: 2025-04-06T03:55:31.954Z (about 1 year ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 27.5 MB
- Stars: 38
- Watchers: 2
- Forks: 4
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# LLMOps - Language Model Operations
## Overview
This repository contains two Python examples designed for fine-tuning, deploying and scaling language models using Modal, Langchain, Fastapi, VLLM and Hugging Face's Transformers.
## Author
[Prince Canuma](https://www.linkedin.com/in/prince-canuma/) - An MLOPs Engineer and founder at [Kulissiwa](https://www.kulissiwa.com/). Previously, he worked as a ML Engineer at neptune.ai. He is passionate about MLOps, Deep Learning, and Software Engineering.
## Contributions
Contributions to this project are welcome. Please follow the standard procedures for submitting issues and pull requests.
## License
This project is licensed under the MIT License - see the LICENSE file for details.