Instructions to use glasses/resnet26d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use glasses/resnet26d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="glasses/resnet26d") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("glasses/resnet26d", device_map="auto") - Notebooks
- Google Colab
- Kaggle
commit files to HF hub
Browse files
README.md
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#resnet26d
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Implementation of ResNet proposed in [Deep Residual Learning for Image
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Recognition](https://arxiv.org/abs/1512.03385)
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# resnet26d
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Implementation of ResNet proposed in [Deep Residual Learning for Image
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Recognition](https://arxiv.org/abs/1512.03385)
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