Instructions to use hvlgo/resnet18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hvlgo/resnet18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hvlgo/resnet18")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hvlgo/resnet18") model = AutoModel.from_pretrained("hvlgo/resnet18", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download meta.yaml from hvlgo/resnet18: direct link, hf CLI and curl.
- Browser
- Download file 33 Bytes
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https://huggingface.co/hvlgo/resnet18/resolve/main/meta.yaml
- Command line
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hf download hf://hvlgo/resnet18/meta.yaml
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curl -L -o meta.yaml https://huggingface.co/hvlgo/resnet18/resolve/main/meta.yaml
33 Bytes
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| output: | |
| - 96 | |
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