Instructions to use nvidia/mit-b4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/mit-b4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nvidia/mit-b4") 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-b4") model = AutoModelForImageClassification.from_pretrained("nvidia/mit-b4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d9ccfb24d0ce11549bf3a08baef2546aaa23720fa9fb923664ec28adcfdfe95
- Size of remote file:
- 246 MB
- SHA256:
- 1cddf0f9ed0b7f1639a8f5e339c177673685df3e2e3c9575a649eb15bcf68a55
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