Instructions to use chaeliwon/vit-base-beans-demo-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chaeliwon/vit-base-beans-demo-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="chaeliwon/vit-base-beans-demo-v5") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("chaeliwon/vit-base-beans-demo-v5") model = AutoModelForImageClassification.from_pretrained("chaeliwon/vit-base-beans-demo-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from chaeliwon/vit-base-beans-demo-v5: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/chaeliwon/vit-base-beans-demo-v5/resolve/main/training_args.bin
- Command line
-
hf download hf://chaeliwon/vit-base-beans-demo-v5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/chaeliwon/vit-base-beans-demo-v5/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 3e73e461db0f2dad223e5791aebb7292832b61f3488baf6ca02c1fb4365ecb15
- Size of remote file:
- 5.11 kB
- SHA256:
- d9684a87ee9c8689595c489c9fdb2235ffa44b5cfd33d6b475b2a6cadd818dad
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