Instructions to use mwalmsley/zoobot-encoder-euclid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use mwalmsley/zoobot-encoder-euclid with timm:
import timm model = timm.create_model("hf_hub:mwalmsley/zoobot-encoder-euclid", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cb46ba8f19f8991439b60d2bcf63a75330fb1a7fa846f4e9a09f4031b5999a5
- Size of remote file:
- 59.9 MB
- SHA256:
- 84a09e21e4eb98655e05b7575784c711433859c272f9be4f4123cc2e35af11ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.