Image Segmentation
Transformers
Safetensors
multilingual
sa2va_chat
image-feature-extraction
Sa2VA
custom_code
Instructions to use kumuji/Sa2VA-i-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kumuji/Sa2VA-i-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="kumuji/Sa2VA-i-8B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kumuji/Sa2VA-i-8B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: update pipeline tag, add paper/code links and detailed info
#1
by nielsr HF Staff - opened
This PR significantly enhances the model card for Sa2VA-i by:
- Updating Metadata: Correcting the
pipeline_tagfromimage-text-to-texttoimage-segmentationto accurately reflect its capabilities in language-guided dense grounding and video object segmentation. - Adding Paper Link: Linking to the official Hugging Face paper page for easy access to the research.
- Adding GitHub Link: Providing a direct link to the associated GitHub repository for code access.
- Enriching Content: Incorporating a comprehensive overview from the paper abstract and the GitHub README, including:
- Authors and affiliations
- A teaser image
- Key improvements and detailed explanations
- Performance highlights and competition results
- A model zoo with links to other Sa2VA-i models
- Comprehensive citation information for both Sa2VA-i and the original Sa2VA.
These changes provide a much more informative and accessible model card for the Hugging Face community.
kumuji changed pull request status to merged