umbertocappellazzo / PETL_AST

This is the official repository of the papers "Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers" and "Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of Adapters".

Date Created 2023-12-02 (11 months ago)

Commits 53 (last one 3 months ago)

Stargazers 36 (0 this week)

Watchers 6 (0 this week)

Forks 3

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RepositoryStats indexes 584,353 repositories, of these umbertocappellazzo/PETL_AST is ranked #532,160 (9th percentile) for total stargazers, and #297,856 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #103,938/116,326.

umbertocappellazzo/PETL_AST is also tagged with popular topics, for these it's ranked: transfer-learning (#289/310), audio-processing (#254/280), lora (#244/273)

Other Information

Homepage URL: https://arxiv.org/abs/2312.03694

All Topics

lora adapter prompt-tuning audio-processing transfer-learning mixture-of-experts mixture-of-adapters audio-spectrogram-transformer parameter-efficient-fine-tuning

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53 commits on the default branch (main) since jan '22

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The only known language in this repository is Python

updated: 2024-11-14 @ 04:56pm, id: 726425219 / R_kgDOK0xegw