Instructions to use CollectionStudio/sam2-hiera-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CollectionStudio/sam2-hiera-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="CollectionStudio/sam2-hiera-large")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("CollectionStudio/sam2-hiera-large") model = AutoModel.from_pretrained("CollectionStudio/sam2-hiera-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ac94f3b242c5a6b13893ec8c4ed687c96b3f9b1a97556552e17b2cdac5a4a4f
- Size of remote file:
- 898 MB
- SHA256:
- 7442e4e9b732a508f80e141e7c2913437a3610ee0c77381a66658c3a445df87b
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