Instructions to use SummerChiam/rust_image_classification_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerChiam/rust_image_classification_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SummerChiam/rust_image_classification_4") 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("SummerChiam/rust_image_classification_4") model = AutoModelForImageClassification.from_pretrained("SummerChiam/rust_image_classification_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SummerChiam/rust_image_classification_4: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/SummerChiam/rust_image_classification_4/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SummerChiam/rust_image_classification_4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SummerChiam/rust_image_classification_4/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 1af82780e74e22798215132b1a7a21a607032cc6033589ae79a5419b674fe664
- Size of remote file:
- 343 MB
- SHA256:
- de9bb5abd1f62880ec3c4398ac5701ecb20771302b2e9bdad40e126d1c3c4f6b
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