Instructions to use boomsakala/sam_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boomsakala/sam_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="boomsakala/sam_model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("boomsakala/sam_model") model = AutoModel.from_pretrained("boomsakala/sam_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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