Instructions to use hercapa/my_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hercapa/my_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hercapa/my_model") 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("hercapa/my_model") model = AutoModelForImageClassification.from_pretrained("hercapa/my_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99d4eadbd005a78101c80388f4f01666003bb36705c94896c47ecef38d0e5072
- Size of remote file:
- 3.58 kB
- SHA256:
- 08ce30dd2e6dc950179e7f3237ae9e10ec6b6392351f96be26563e592e973a48
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