Instructions to use microsoft/resnet-18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/resnet-18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/resnet-18") 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("microsoft/resnet-18") model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-18") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
2f536bd
1
Parent(s): 0695923
Add TF weights (#1)
Browse files- Add TF weights (ea4191cd0ee345d27d72bf01001bdbddc41926a2)
- 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 sha256:64320beb5ab72e9819844eb576a38ed9ffbd6edd73dc752a9c920801fb025c96
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size 46933112
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