Instructions to use nvidia/mit-b3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/mit-b3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nvidia/mit-b3") 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-b3") model = AutoModelForImageClassification.from_pretrained("nvidia/mit-b3", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19835032682519190d543045536e3a22e5d2e5c5e12522ac7acd07b3bc09219b
- Size of remote file:
- 179 MB
- SHA256:
- b77280dc4ddb4940d20d7dfff1773d48892f982724bb5cbc1e412c9a1ef20958
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