Instructions to use timm/sam2_hiera_base_plus.fb_r896_2pt1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/sam2_hiera_base_plus.fb_r896_2pt1 with timm:
import timm model = timm.create_model("hf_hub:timm/sam2_hiera_base_plus.fb_r896_2pt1", pretrained=True) - Transformers
How to use timm/sam2_hiera_base_plus.fb_r896_2pt1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/sam2_hiera_base_plus.fb_r896_2pt1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/sam2_hiera_base_plus.fb_r896_2pt1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Model card for sam2_hiera_base_plus.fb_r896_2pt1
timm SAM2 (HieraDet image encoder only) weights from https://huggingface.co/facebook/sam2.1-hiera-base-plus
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