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
fg-mindee commited on
Commit ·
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Parent(s): 494fb5f
feat: Added ONNX model
Browse files- README.md +1 -0
- model.onnx +3 -0
README.md
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tags:
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- image-classification
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- pytorch
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datasets:
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- imagenette
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tags:
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- image-classification
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- pytorch
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- onnx
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datasets:
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- imagenette
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model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:650de4290098363e32a9db28b684a4c35ec744503803289edbb3f0fe3b30beab
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size 88986885
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