qualcomm / efficient-transformers
This library empowers users to seamlessly port pretrained models and checkpoints on the HuggingFace (HF) hub (developed using HF transformers library) into inference-ready formats that run efficiently on Qualcomm Cloud AIxx (AI100, AI200 and so on) accelerators.
Why this job: matched by what the repo talks about: inference, model, library, efficient
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit today
- Stars
- 102
- On GitHub
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest tag
- release/v1.23.0
- Released 54 days ago
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- 28
- Last 90 days
- Issues
- 70% closed
- 6 still open
- Pull requests
- 841 merged
- 67 waiting
- Releases
- 7
- 5 in the last year
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More: languages, topics and project record
Languages
- Python 100%
- Shell <1%
- Dockerfile <1%
- Makefile <1%
Topics
- accelerator
- ai
- cloud
- llm
- qualcomm
Project record
- JobLocal LLMs
- StatusListed
- Commits560
- Forks116
- Watching5
- Stars in 28 days+1
- CreatedMar 30, 2024
- First seen by usNov 7, 2026
- CheckedNov 12, 2026