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:
- 26b79769529d647d1cf202ab8f4b44c57c13cf9c18d3a60b3aecd23548ed0c4a
- Size of remote file:
- 98.9 MB
- SHA256:
- b3ad4dd552f9e1b871f46666f39187414133b861e3d07eda016600230f8a1ad6
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