Mattral/production-vlm-engineering
Reproducible, production-grade pipelines for modern multimodal vision systems. Efficient VLM adaptation · Embedding-space drift detection · Edge inference · Robustness & safety
- Stars
- 58
- Forks
- 0
- Open issues
- 0
- Last push
- 2mo ago
production-vlm-engineering star history
-2 this week
About production-vlm-engineering
production-vlm-engineering is a free, open-source AI inference tool by Mattral, written mainly in Python. Reproducible, production-grade pipelines for modern multimodal vision systems. Efficient VLM adaptation · Embedding-space drift detection · Edge inference · Robustness & safety. It has 58 GitHub stars and 0 forks, and was last updated 2mo ago. It's released under the MIT license, a standard open-source license. According to the project, it runs on a regular CPU without a GPU.
- License
- MIT
- Commercial use
- Commercial OK
- Language
- Python
- Stars
- 58
- Last update
- 2mo ago
- Runs on Mac
- Not stated
- GPU
- Not needed (runs on CPU)
- Paid API key
- Not stated
- Self-hostable
- Not stated
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production-vlm-engineering FAQ
Can I use production-vlm-engineering commercially?
Yes. MIT is a permissive license: commercial use is allowed as long as you keep the license notice. This is a plain-English summary, not legal advice.
Is production-vlm-engineering free?
Yes. production-vlm-engineering is open source and free to use. It's released under the MIT license, a standard open-source license.
Does production-vlm-engineering run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does production-vlm-engineering need a GPU?
No. According to the project, production-vlm-engineering runs on a regular CPU.
Is production-vlm-engineering still maintained?
It was last updated 2mo ago. Check recent issues on GitHub to judge how active it is.
What are alternatives to production-vlm-engineering?
Similar free, open-source tools include sglang, inference, PowerInfer, airllm.
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