Instructions to use microsoft/resnet-26 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/resnet-26 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/resnet-26") 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-26") model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-26") - Notebooks
- Google Colab
- Kaggle
Add TF weights
#1
by amyeroberts - opened
- 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:f1f4dc9edd6f6a5c62a4c49947f4ad900fbe71aa8f2951e3f770f7b4476a59f3
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size 64281824
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