Instructions to use glasses/resnet152 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use glasses/resnet152 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="glasses/resnet152") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("glasses/resnet152", dtype="auto") - Notebooks
- Google Colab
- Kaggle
add model
Browse files- config.json +1 -0
- pytorch_model.bin +3 -0
config.json
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:badde583b54eecfab4be6f85e23ffa937c462a0fab556f6d8515143511c04f1c
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size 241730227
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