# qualcomm/efficient-transformers

<https://repo.masters-masters.com/en/repos/qualcomm/efficient-transformers>

[Home](https://repo.masters-masters.com/en) › [qualcomm](https://repo.masters-masters.com/en/owners/qualcomm) › [efficient-transformers](https://repo.masters-masters.com/en/repos/qualcomm/efficient-transformers)

qualcomm/efficient-transformers has 102 stars on GitHub. Its RepoMasters card: Prototype tier. This library empowers users to seamlessly port pretrained…

| Field | Value |
| --- | --- |
| Owner | [qualcomm](https://repo.masters-masters.com/en/owners/qualcomm) |
| Stars | 102 |
| Forks | 114 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2024 |
| Topics | accelerator, ai, cloud, llm, qualcomm |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [qualcomm/efficient-transformers](https://github.com/qualcomm/efficient-transformers) |

## Repository

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.

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.