SDFT - Pytorch
Project description
SDFT - Pytorch (wip)
Explorations into the proposed SDFT, Self-Distillation Enables Continual Learning, from Shenfeld et al. of MIT
Citations
@misc{shenfeld2026selfdistillationenablescontinuallearning,
title = {Self-Distillation Enables Continual Learning},
author = {Idan Shenfeld and Mehul Damani and Jonas Hübotter and Pulkit Agrawal},
year = {2026},
eprint = {2601.19897},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2601.19897},
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
sdft_pytorch-0.0.3.tar.gz
(4.8 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file sdft_pytorch-0.0.3.tar.gz.
File metadata
- Download URL: sdft_pytorch-0.0.3.tar.gz
- Upload date:
- Size: 4.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.25
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
32914decd76b6ab284a5a4e782ce2d9f72fae7fd011427175d348f15174f44c6
|
|
| MD5 |
f1d73c0dc3d4927e6b1cfabfd865cd9a
|
|
| BLAKE2b-256 |
706749675940e65459f3f3a392a4df9339b841458890d7c241c0bcbcb2215ff1
|
File details
Details for the file sdft_pytorch-0.0.3-py3-none-any.whl.
File metadata
- Download URL: sdft_pytorch-0.0.3-py3-none-any.whl
- Upload date:
- Size: 4.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.25
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b8c29a141dc2c88650a4bae2e717de01e8760d7bd3fdb3ffcf700a6fe2f44018
|
|
| MD5 |
1cc13d2bfb11b0a790bd93224779f1ba
|
|
| BLAKE2b-256 |
96cdeffa2cff6f7d15f56ecc0d724769f2bda6c4bb4e2b2f7a5bdb15b2b2b2e8
|