Instructions to use JLB-JLB/Model_folder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JLB-JLB/Model_folder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JLB-JLB/Model_folder") 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("JLB-JLB/Model_folder") model = AutoModelForImageClassification.from_pretrained("JLB-JLB/Model_folder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fe46b4c155cb3ddee87dae83fdccce331ae0dc383bcf700cb87a9da09a4b1bf
- Size of remote file:
- 4.54 kB
- SHA256:
- 1c4abf93990c82b841efb6a8f8aab603e55e9c850cfab05d41e1fd822a546a6d
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