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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("danilobukvic/sam3-text-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vision_encoder_int4.onnx from danilobukvic/sam3-text-onnx: direct link, hf CLI and curl.
- Browser
- Download file 5.83 MB
-
https://huggingface.co/danilobukvic/sam3-text-onnx/resolve/main/vision_encoder_int4.onnx
- Command line
-
hf download hf://danilobukvic/sam3-text-onnx/vision_encoder_int4.onnx
-
curl -L -o vision_encoder_int4.onnx https://huggingface.co/danilobukvic/sam3-text-onnx/resolve/main/vision_encoder_int4.onnx
5.83 MB
- Xet hash:
- 26a8a62102edade9c109332bb62509022ff7b1b370324a0b1e1a91c7fa447d04
- Size of remote file:
- 5.83 MB
- SHA256:
- 88edb4602b7e7b2aa282543dea0b25a253bb13d5d7d5debbd19c2fb5e7941ae7
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