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", device_map="auto") 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:
- db68fd5272b2a174a90043a2c69303924459846c9c78d448dcb9b76130e7a9c0
- Size of remote file:
- 343 MB
- SHA256:
- 25dc23ed2e2daaa9d65f217c2f92cc025e12783db32fcd5d87e1f3d279d3331c
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