yoshitomo-matsubara / torchdistill

A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

yoshitomo-matsubara
yoshitomo-matsubara
Date Created 2019-12-18 (4 years ago)
Commits 1,538 (last one about a month ago)
Stargazers 1,393 (1 this week)
Watchers 19 (0 this week)
Forks 131
License mit
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RepositoryStats indexes 584,353 repositories, of these yoshitomo-matsubara/torchdistill is ranked #37,342 (94th percentile) for total stargazers, and #116,307 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #5,730/116,326.

yoshitomo-matsubara/torchdistill is also tagged with popular topics, for these it's ranked: pytorch (#638/5948),  nlp (#275/2400),  natural-language-processing (#183/1411),  object-detection (#133/1158),  transformer (#89/1000),  semantic-segmentation (#39/512),  image-classification (#48/393),  knowledge-distillation (#14/157)

Other Information

There have been 25 releases, the latest one was published on 2024-08-13 (3 months ago) with the name A new KD method, new benchmark results, and updated YAML constructors.

Homepage URL: https://yoshitomo-matsubara.net/torchdistill/

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yoshitomo-matsubara/torchdistill

updated: 2024-11-20 @ 12:17am, id: 228891845 / R_kgDODaScxQ