Instructions to use hamriver/Hamilton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamriver/Hamilton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hamriver/Hamilton") 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("hamriver/Hamilton") model = AutoModelForImageClassification.from_pretrained("hamriver/Hamilton", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c05c6595011b3be18121afcee8e26c7a89f781e96f45623ac9915741f3b29b4
- Size of remote file:
- 5.3 kB
- SHA256:
- 5e7eee7e15b165e36846ccca24603ecd61a1e3a9c01f30892c29e4b8c16631eb
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