Instructions to use wangzeze/V2-SAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wangzeze/V2-SAM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="wangzeze/V2-SAM")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wangzeze/V2-SAM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from wangzeze/V2-SAM: direct link, hf CLI and curl.
- Browser
- Download file 181 Bytes
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https://huggingface.co/wangzeze/V2-SAM/resolve/main/README.md
- Command line
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hf download hf://wangzeze/V2-SAM/README.md
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curl -L -o README.md https://huggingface.co/wangzeze/V2-SAM/resolve/main/README.md
181 Bytes
metadata
license: apache-2.0
tags:
- multimodal
- vision-language
- segmentation
- ego-centric
language:
- en
library_name: transformers
pipeline_tag: image-segmentation