# ShiZhengyan/DePT

<https://repo.masters-masters.com/en/repos/ShiZhengyan/DePT>

[Home](https://repo.masters-masters.com/en) › [ShiZhengyan](https://repo.masters-masters.com/en/owners/ShiZhengyan) › [DePT](https://repo.masters-masters.com/en/repos/ShiZhengyan/DePT)

ShiZhengyan/DePT has 101 stars on GitHub. Its RepoMasters card: Prototype tier. \[ICLR 2024\] This is the repository for the paper titled "DePT: Decomposed…

| Field | Value |
| --- | --- |
| Owner | [ShiZhengyan](https://repo.masters-masters.com/en/owners/ShiZhengyan) |
| Stars | 101 |
| Forks | 15 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2023 |
| Topics | fine-tuning, language-model, large-language-models, natural-language-processing, parameter-efficient-tuning, peft, prompt-tuning, parameter-efficient-fine-tuning, nlp, nlp-machine-learning |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [ShiZhengyan/DePT](https://github.com/ShiZhengyan/DePT) |

## Repository

\[ICLR 2024\] This is the repository for the paper titled "DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning"

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.