Instructions to use nvidia/mit-b2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/mit-b2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nvidia/mit-b2") 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("nvidia/mit-b2") model = AutoModelForImageClassification.from_pretrained("nvidia/mit-b2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4748f31cb06c25ebd196bfd4640d8b170839ba007905cfe77dd773685d7479b2
- Size of remote file:
- 99.3 MB
- SHA256:
- 3034758dedb4f3e3436bfabaa3043ca7ccb20c24cc202e6d2670c962af772ede
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