Instructions to use Bylaw/bp-template-classification-dit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bylaw/bp-template-classification-dit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, BylawBeitForImageClassification processor = AutoImageProcessor.from_pretrained("Bylaw/bp-template-classification-dit") model = BylawBeitForImageClassification.from_pretrained("Bylaw/bp-template-classification-dit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Bylaw/bp-template-classification-dit: direct link, hf CLI and curl.
- Browser
- Download file 686 MB
-
https://huggingface.co/Bylaw/bp-template-classification-dit/resolve/main/optimizer.pt
- Command line
-
hf download hf://Bylaw/bp-template-classification-dit/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Bylaw/bp-template-classification-dit/resolve/main/optimizer.pt
686 MB
- Xet hash:
- 68a7abe25fb118b553f93956fca7984eae30bb7f05d49102f527a34923dabdb4
- Size of remote file:
- 686 MB
- SHA256:
- 48940705d7d85a05669abffdd78add551f9682e8a663c3530e7d3f030379ee99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.