Instructions to use microsoft/resnet-34 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/resnet-34 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/resnet-34") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("microsoft/resnet-34") model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-34", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (303bcf9e5dff618d5ca948b1c0dbc6f1176679aa) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>4d180fb
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Add TF weights (#1)
- Add TF weights (ceb187723451886cac699b91b38e43fdd2db12a3)4eb2538
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Update README.md
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Update README.md
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Add model card
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Add feature extractor
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Add model
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initial commit
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