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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Subh775/Seg-Basil-rfdetr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
Verified signature6644c23
-
Update README.md
Verified signature16e44f5
-
Update README.md
Verified signature1aa4144
-
Update README.md
Verified signature5fa9373 -
Update README.md
Verified signature7543baf -
Update README.md
Verified signature094c001 -
Update README.md
Verified signaturec91a1e4 -
Update README.md
Verified signaturef34302e -
Update README.md
Verified signature7ea36f9 -
Update README.md
Verified signatureacad14b -
Update README.md
Verified signature175b769
-
Update README.md
Verified signatured3cc231 -
Update README.md
Verified signatureb868dd0 -
Update README.md
Verified signature6d7b203 -
Update README.md
Verified signature7692574 -
Create README.md
Verified signature135114c -
Upload Rfdetr seg v2 - 9 files
Verified signatured851e3e -
initial commit
Verified signature77fe63e