Instructions to use facebook/sam-vit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/sam-vit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="facebook/sam-vit-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("facebook/sam-vit-base") model = AutoModelForMaskGeneration.from_pretrained("facebook/sam-vit-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from facebook/sam-vit-base: direct link, hf CLI and curl.
- Browser
- Download file 375 MB
-
https://huggingface.co/facebook/sam-vit-base/resolve/main/model.safetensors
- Command line
-
hf download hf://facebook/sam-vit-base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/facebook/sam-vit-base/resolve/main/model.safetensors
375 MB
- Xet hash:
- b6eab3190beb72c24814504b531617336f3c2eb4ba8a948c35f4590c08f061d7
- Size of remote file:
- 375 MB
- SHA256:
- 892c410e496344e527255ccdcb2cb7244a609acb5389c7c4fdba1288f861c579
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