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")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("microsoft/resnet-34") model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-34") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
4eb2538
1
Parent(s): f5f4f59
Add TF weights (#1)
Browse files- Add TF weights (ceb187723451886cac699b91b38e43fdd2db12a3)
- 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:ae6a2847c51006462492cbbcdb571b206ac8d756abf04af4167ab7a1d7574740
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size 87494664
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