Instructions to use frgfm/darknet53 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frgfm/darknet53 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="frgfm/darknet53") 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/darknet53", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40826320b37e96e030b588e72c38b9a1454eea65ede8d328eabaeaa18c3959d9
- Size of remote file:
- 163 MB
- SHA256:
- 2004fde5ac3dcf168b5cdfa18474ff67e419da6a257ea719f33290585e498ec5
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