Instructions to use frgfm/repvgg_a0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frgfm/repvgg_a0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="frgfm/repvgg_a0") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("frgfm/repvgg_a0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecd72f79c0b7fb14dc104c0dee2f6705fe7786038bd53119eeab97899600d1d6
- Size of remote file:
- 89 MB
- SHA256:
- 650de4290098363e32a9db28b684a4c35ec744503803289edbb3f0fe3b30beab
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