Instructions to use frgfm/cspdarknet53_mish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frgfm/cspdarknet53_mish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="frgfm/cspdarknet53_mish") 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/cspdarknet53_mish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 512cd22485c5142dc690b2baef3d42e32384fad4c6301b5ac8b1beca5a999b94
- Size of remote file:
- 107 MB
- SHA256:
- 6f45743ee8f8f7c410042a7b8b0b269766e01260484729edad7f811ef50917a1
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