Instructions to use h2thez3/sam_busi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use h2thez3/sam_busi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="h2thez3/sam_busi")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("h2thez3/sam_busi") model = AutoModelForMaskGeneration.from_pretrained("h2thez3/sam_busi") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoProcessor, AutoModelForMaskGeneration
processor = AutoProcessor.from_pretrained("h2thez3/sam_busi")
model = AutoModelForMaskGeneration.from_pretrained("h2thez3/sam_busi")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="h2thez3/sam_busi")