Instructions to use tiya1012/vit-base-beans-55 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiya1012/vit-base-beans-55 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tiya1012/vit-base-beans-55") 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("tiya1012/vit-base-beans-55") model = AutoModelForImageClassification.from_pretrained("tiya1012/vit-base-beans-55", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tiya1012/vit-base-beans-55: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/tiya1012/vit-base-beans-55/resolve/main/training_args.bin
- Command line
-
hf download hf://tiya1012/vit-base-beans-55/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tiya1012/vit-base-beans-55/resolve/main/training_args.bin
4.41 kB
- Xet hash:
- 9992530dc95d620a01438b605fd3b5b6b748aef5a73096087f7bca98ff61636e
- Size of remote file:
- 4.41 kB
- SHA256:
- 0327bb4d10ed598fe94d4efce470552f1d37ba24c2b6fd0de143ed635afdcaf3
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