Instructions to use danelcsb/sam2_hiera_base_plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danelcsb/sam2_hiera_base_plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="danelcsb/sam2_hiera_base_plus")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("danelcsb/sam2_hiera_base_plus") model = AutoModel.from_pretrained("danelcsb/sam2_hiera_base_plus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from danelcsb/sam2_hiera_base_plus: direct link, hf CLI and curl.
- Browser
- Download file 90 Bytes
-
https://huggingface.co/danelcsb/sam2_hiera_base_plus/resolve/main/processor_config.json
- Command line
-
hf download hf://danelcsb/sam2_hiera_base_plus/processor_config.json
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curl -L -o processor_config.json https://huggingface.co/danelcsb/sam2_hiera_base_plus/resolve/main/processor_config.json
90 Bytes
| { | |
| "point_pad_value": -10, | |
| "processor_class": "Sam2Processor", | |
| "target_size": 1024 | |
| } | |