Instructions to use SummerChiam/rust_image_classification_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerChiam/rust_image_classification_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SummerChiam/rust_image_classification_5") 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_5") model = AutoModelForImageClassification.from_pretrained("SummerChiam/rust_image_classification_5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SummerChiam/rust_image_classification_5: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/SummerChiam/rust_image_classification_5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SummerChiam/rust_image_classification_5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SummerChiam/rust_image_classification_5/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 151323f03157b571083f6e83cb44942dd5614d81a5c8ec60a6b6f4b83820dbc6
- Size of remote file:
- 343 MB
- SHA256:
- 9ac029bbee4821d128617eb79251786f7a67dabee766ffa269b190db282b2d16
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