Image Classification
Transformers
PyTorch
TensorBoard
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use fumi13/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fumi13/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fumi13/vit-base-beans") 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("fumi13/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("fumi13/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fumi13/vit-base-beans: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/fumi13/vit-base-beans/resolve/main/training_args.bin
- Command line
-
hf download hf://fumi13/vit-base-beans/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fumi13/vit-base-beans/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- 66bc875a65d30036769ca4b410e96e4ebcf6a73870ace6b312d0509db7973891
- Size of remote file:
- 3.44 kB
- SHA256:
- 99b49ffbebf0f91bad960e011f43ae8b34f915cd66bcfec38b2d4273850b32a2
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