Instructions to use hgarg/fruits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hgarg/fruits with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hgarg/fruits") 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("hgarg/fruits") model = AutoModelForImageClassification.from_pretrained("hgarg/fruits") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 041e4ce680492a22b4c8c01fa1267543417ca014fb5119b345da751001527694
- Size of remote file:
- 343 MB
- SHA256:
- 669b2d2d9a9da4ca638ae5bfe8f1cab3a0cb464df376eb9eb7570d552e4a9663
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