# AGI-Edgerunners/LLM-Adapters

<https://repo.masters-masters.com/en/repos/AGI-Edgerunners/LLM-Adapters>

[Home](https://repo.masters-masters.com/en) › [AGI-Edgerunners](https://repo.masters-masters.com/en/owners/AGI-Edgerunners) › [LLM-Adapters](https://repo.masters-masters.com/en/repos/AGI-Edgerunners/LLM-Adapters)

AGI-Edgerunners/LLM-Adapters has 1,238 stars on GitHub. Its RepoMasters card: Beta tier. Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for…

| Field | Value |
| --- | --- |
| Owner | [AGI-Edgerunners](https://repo.masters-masters.com/en/owners/AGI-Edgerunners) |
| Stars | 1,238 |
| Forks | 117 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2023 |
| Topics | adapters, fine-tuning, large-language-models, parameter-efficient |
| Tier | [Beta (700 to 1,999 ★)](https://repo.masters-masters.com/en/ranks/box_office) |
| View on GitHub | [AGI-Edgerunners/LLM-Adapters](https://github.com/AGI-Edgerunners/LLM-Adapters) |

## Repository

Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"

The tier for repos with 700 to 1,999 ★. Published odds per card pulled: 6%. Rarity: Rare.

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