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:
- 3bf4ede443a0aae898dfcc399de4c2bbd5e0b4ce4b508859497a66ebc151ea2f
- Size of remote file:
- 343 MB
- SHA256:
- 41056a1ddb3f2c3980bd63ba00fd877a46170e6bee64d1b13e9423d392ddb7c0
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