Instructions to use SummerChiam/rust_image_classification_12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerChiam/rust_image_classification_12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SummerChiam/rust_image_classification_12") 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_12") model = AutoModelForImageClassification.from_pretrained("SummerChiam/rust_image_classification_12", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SummerChiam/rust_image_classification_12: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/SummerChiam/rust_image_classification_12/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SummerChiam/rust_image_classification_12/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SummerChiam/rust_image_classification_12/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 0084f6194f8d6e2c88f24fdbd035d6ec5102e8c1a9ec12dc3c3e00a15272435d
- Size of remote file:
- 343 MB
- SHA256:
- 23b78efad4028adba6aac08de534f520a699e676a8f9216826393a86e0534cda
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.