Instructions to use adwod/ViT_bluetab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adwod/ViT_bluetab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="adwod/ViT_bluetab") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("adwod/ViT_bluetab") model = AutoModelForImageClassification.from_pretrained("adwod/ViT_bluetab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from adwod/ViT_bluetab: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/adwod/ViT_bluetab/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://adwod/ViT_bluetab/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/adwod/ViT_bluetab/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 8a2301e4278604db28e7645090e210cc0d340add522ea4b7961bd920e7ee71f2
- Size of remote file:
- 343 MB
- SHA256:
- 947db0200571ec9115695ba754599f399070162edf99eaa0a6ae6aa2a3003a5e
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