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:
- 5d2c99412bcd4e5c4086d0ffa705bb19e92cec24415af018bcc61208a6765ba2
- Size of remote file:
- 178 MB
- SHA256:
- 8de18cbe1efd929b0caa6b54edb92a4524e10e4d6f9468645933af15f5b2923e
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