Instructions to use facebook/regnet-x-008 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-008 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-008") 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("facebook/regnet-x-008") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-008") - Notebooks
- Google Colab
- Kaggle
Add TF weights (#1)
Browse files- Add TF weights (3cdad32ae66c00c4dce68d4b1f6a3aa661f63179)
- 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 sha256:10221fcf89a7ee7b940c2bf9c75159a45aceafb0848bbe4a41cf5815c8b9b53f
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size 29502160
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