Instructions to use s23deepak/streaming-vlm-qwen3-rocm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s23deepak/streaming-vlm-qwen3-rocm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("s23deepak/streaming-vlm-qwen3-rocm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, library name, and paper links
#1
by nielsr HF Staff - opened
Hi,
This PR improves the model card by:
- Adding the
video-text-to-textpipeline tag for better discoverability. - Adding the
library_name: transformersmetadata since the model is compatible with thetransformerslibrary. - Linking the model to the original research paper: StreamingVLM: Real-Time Understanding for Infinite Video Streams.
- Providing links to the official project page and original source code.
Please let me know if you have any questions!
s23deepak changed pull request status to merged
Thanks for the model card.