tinygrad Image Models
Project description
tinygrad Image Models
A collection of vision models implemented in tinygrad, in a similar vein to timm.
Mostly targeting models trained on Imagenet-1k, and other models that are fast on resource-constrained devices.
Models
- ShuffleNetV2 - paper code
- GhostNetV2 - paper code
- FocalNet - paper code
- FastViT - paper code
- RepViT - paper code
TODO
- For models that can be reparameterized, add that functionality
- Training
License
See LICENSE.
Certain parts of the code are adapted from the original implementations, but they should all be under permissive licenses.
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
tgim-0.0.0.tar.gz
(13.3 kB
view details)
Built Distribution
tgim-0.0.0-py3-none-any.whl
(17.4 kB
view details)
File details
Details for the file tgim-0.0.0.tar.gz.
File metadata
- Download URL: tgim-0.0.0.tar.gz
- Upload date:
- Size: 13.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | c03eb49cdf790123fd0e5d5d0e47651c4d462c54d84bc8a13a6e62720ea30130 |
|
| MD5 | 17967365bc38396759f4097b124882ed |
|
| BLAKE2b-256 | 442d3cb485e653ee58ae3a238e4199ee93961a3643fe0f750ad396bee48958f7 |
File details
Details for the file tgim-0.0.0-py3-none-any.whl.
File metadata
- Download URL: tgim-0.0.0-py3-none-any.whl
- Upload date:
- Size: 17.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 9511d0eb54939bc3e031f8216ae62c92189713196105d56914171f738505fde3 |
|
| MD5 | 0f96c2744d143594f37ecb963f2e753e |
|
| BLAKE2b-256 | 9c28c60345edddaaafb00fa6f470cbb2a0f2a8d5d2efc7491d3ae0f9506b33ff |
