Instructions to use nvidia/mit-b1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/mit-b1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nvidia/mit-b1") 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-b1") model = AutoModelForImageClassification.from_pretrained("nvidia/mit-b1") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
52eb2a1
1
Parent(s): 73b65a0
Add TF weights (#1)
Browse files- Add TF weights (17ebbf89e3365940230e1d3a9bb1720b63ae2365)
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:163057aa0e923a68dda4795e764e74790efa0c863f281f35fb75530a5d70aca7
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size 54919784
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