Instructions to use DiffusionWave/sam3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DiffusionWave/sam3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="DiffusionWave/sam3")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("DiffusionWave/sam3") model = AutoModel.from_pretrained("DiffusionWave/sam3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from DiffusionWave/sam3: direct link, hf CLI and curl.
- Browser
- Download file 3.64 MB
-
https://huggingface.co/DiffusionWave/sam3/resolve/main/tokenizer.json
- Command line
-
hf download hf://DiffusionWave/sam3/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/DiffusionWave/sam3/resolve/main/tokenizer.json
3.64 MB
File too large to display, you can check the raw version instead.