Instructions to use crapthings/beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crapthings/beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="crapthings/beans") 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("crapthings/beans") model = AutoModelForImageClassification.from_pretrained("crapthings/beans") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- abe2a1471be7179da846b730eb57d011a3e5d11c9c0dcc562efb386102277599
- Size of remote file:
- 343 MB
- SHA256:
- d166a5d0efc2b28874fb962e247c7ca985192407e9a5c68295a071eac2159d8a
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