Instructions to use TalentoTechIA/Hamilton2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalentoTechIA/Hamilton2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TalentoTechIA/Hamilton2") 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("TalentoTechIA/Hamilton2") model = AutoModelForImageClassification.from_pretrained("TalentoTechIA/Hamilton2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 472a76020890e4f763a3801e90dc5bbece1413ec7e2d9d05f280f39e032fd471
- Size of remote file:
- 343 MB
- SHA256:
- 120147ce970d45be7720ca7b4f6ee36aaa3b94da97597a261789108ff541bf3c
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