Instructions to use abelkrw/beans_image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abelkrw/beans_image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="abelkrw/beans_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("abelkrw/beans_image_classification") model = AutoModelForImageClassification.from_pretrained("abelkrw/beans_image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from abelkrw/beans_image_classification: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/abelkrw/beans_image_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://abelkrw/beans_image_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/abelkrw/beans_image_classification/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 8fc606766aeb6436125de33e79d709972b335228edaa7a9e5c64ec6ac455176b
- Size of remote file:
- 343 MB
- SHA256:
- 186867e4675ef18c0fd59b1255f2860e4923737a34d201ea83e8207788d5c131
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