Mask Generation
Transformers
ONNX
sam3
sam-3
image-segmentation
text-promptable
open-vocabulary
concept-segmentation
Instructions to use danilobukvic/sam3-text-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danilobukvic/sam3-text-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="danilobukvic/sam3-text-onnx")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("danilobukvic/sam3-text-onnx", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8751b38c104f4eb874984b54167c16b33e69536d9fb2f7c94564d8f4f707b481
- Size of remote file:
- 1.41 GB
- SHA256:
- 81a6e10185aa8206e3ca4048eacabed96a4ad204b54885d834dbddb6acfed942
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