Instructions to use dmis-lab/Qwen2.5-VL-7B-CVRR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmis-lab/Qwen2.5-VL-7B-CVRR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="dmis-lab/Qwen2.5-VL-7B-CVRR", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dmis-lab/Qwen2.5-VL-7B-CVRR", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Demo for this model on Spaces
Hi @dmis-lab team π€
I'm Linoy from the open-source team at Hugging Face - congrats on CVRR!
We built with an agent an interactive demo app for it on Hugging Face Spaces, running on free ZeroGPU infrastructure: https://huggingface.co/spaces/hugging-apps/cvrr-visual-reasoning
We would love to transfer this demo over to you or your organization - just let me know here which username or org to transfer to. We hope it can give your work more visibility, discoverability and let folks try it out.
In the future, feel free to already ship models with demos included. You can use this one as a blueprint to build by yourself or with the help of an agent - you can load the huggingface-spaces skill on Claude Code, Codex, Pi, etc.
Cheers,
Linoy