Instructions to use yaboidimsum/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yaboidimsum/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="yaboidimsum/image_classification") 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("yaboidimsum/image_classification") model = AutoModelForImageClassification.from_pretrained("yaboidimsum/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from yaboidimsum/image_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/yaboidimsum/image_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://yaboidimsum/image_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/yaboidimsum/image_classification/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 9461e294af4d63dbcb2e310162e8cec0a7999f74b2545de14d6c9b8f7a25c4cf
- Size of remote file:
- 4.09 kB
- SHA256:
- 3ea60441e249d04c38204dc43da6a6ac7247135ce5d5bf1ba0e3c6903069a1df
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