Instructions to use jimjakdiend/Checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jimjakdiend/Checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jimjakdiend/Checkpoints") 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("jimjakdiend/Checkpoints") model = AutoModelForImageClassification.from_pretrained("jimjakdiend/Checkpoints") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24b0a0fdbe376f646f6f31e3201f78d093369042a0bc4e9081d0c62a744410f4
- Size of remote file:
- 4.6 kB
- SHA256:
- 601ead9791baf35b3e024a435c22dbb273ce1c46c42d68fe650aa0d03621e8dd
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