Video-Text-to-Text
Transformers
Safetensors
English
qwen2_5_vl
video-scene-graph
scene-graph-generation
video-understanding
trajectory-aware
perceiver-resampler
qwen2.5-vl
text-generation-inference
Instructions to use UWGZQ/TRASER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UWGZQ/TRASER with Transformers:
# Load model directly from transformers import AutoProcessor, Qwen2_5_VLForConditionalGeneration_Insert processor = AutoProcessor.from_pretrained("UWGZQ/TRASER") model = Qwen2_5_VLForConditionalGeneration_Insert.from_pretrained("UWGZQ/TRASER") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 8da7eee4bd4597f2c3b21b1343f7dd2134c81babed9caf72425f61d78f933ae2
- Size of remote file:
- 1.18 MB
- SHA256:
- 4e79d36fa71535659e478febaba6ce2b4a4c9dedc3fb04db41fa5664149218a0
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