Video-Text-to-Text
Transformers
Safetensors
English
qwen3_5
image-text-to-text
streaming-video
video-understanding
on-policy-distillation
knowledge-distillation
Instructions to use UniX-Lab/StreamOPD-4B-ST-CueGate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UniX-Lab/StreamOPD-4B-ST-CueGate with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("UniX-Lab/StreamOPD-4B-ST-CueGate") model = AutoModelForMultimodalLM.from_pretrained("UniX-Lab/StreamOPD-4B-ST-CueGate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 655d3f6803c619aa34c31a027ce74a315eaa200aad3fca5b968dcdf6485bfba2
- Size of remote file:
- 12.8 MB
- SHA256:
- 5f9e4d4901a92b997e463c1f46055088b6cca5ca61a6522d1b9f64c4bb81cb42
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