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") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
3a0bee8
1
Parent(s): 6feb07d
Add TF weights (#1)
Browse files- Add TF weights (58c91047cfaac9c3c3dea671858596b3f9bdc8c7)
- 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:b77280dc4ddb4940d20d7dfff1773d48892f982724bb5cbc1e412c9a1ef20958
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size 179172768
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