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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 219942e47f99e564cced769b8f2983f6fd901b38c8683083c06e997a708b3089
- Size of remote file:
- 293 MB
- SHA256:
- b89c9156064e926761f29be3f87b160fd34f4c93f1de46593295d155621829a2
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