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:
- a6a4a8fec59edc7c5b3cb54ea000896bc2989a5b6f47a0a7dd84a8c1dbc6d41f
- Size of remote file:
- 96 MB
- SHA256:
- eb6a7bbfe1a13d4d2141900f4c32c50636841def66ca89de50b6b3fa5fde4bf8
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