Image Segmentation
Transformers
TensorBoard
English
Instance_Segmentation
CPU_friendly
Transformers
rfdetr
supervision
roboflow
Eval Results (legacy)
Instructions to use Subh775/Seg-Basil-rfdetr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Subh775/Seg-Basil-rfdetr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Subh775/Seg-Basil-rfdetr")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Subh775/Seg-Basil-rfdetr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint_best_regular.pth from Subh775/Seg-Basil-rfdetr: direct link, hf CLI and curl.
- Browser
- Download file 408 MB
-
https://huggingface.co/Subh775/Seg-Basil-rfdetr/resolve/main/checkpoint_best_regular.pth
- Command line
-
hf download hf://Subh775/Seg-Basil-rfdetr/checkpoint_best_regular.pth
-
curl -L -o checkpoint_best_regular.pth https://huggingface.co/Subh775/Seg-Basil-rfdetr/resolve/main/checkpoint_best_regular.pth
408 MB
- Xet hash:
- bd5f10eab490b0b17f15f147360ccf0558f268580b10b7b5d8b42e76b286312d
- Size of remote file:
- 408 MB
- SHA256:
- c767f2142d156e319c01a3dabc11370fb620ace39729d214d629904a60026615
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