Instructions to use microsoft/resnet-101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/resnet-101 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/resnet-101") 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-101") model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-101") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fd4ff38c389a6630f8a39391bc715a7817cd2da5a6935982dd35b3601d2dc44
- Size of remote file:
- 179 MB
- SHA256:
- 9040077087c4420a94fd75ddbea596606faa777d1f23cd496dc970cd89f1c5dd
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