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:
- 8509e8c9e0f401c857d1f2886b2f90be808462127daad652b7a50cad9763f347
- Size of remote file:
- 3.97 MB
- SHA256:
- bea771d46e14045b24a554333dbc07d27292f5927b15a2b3f2dc4ab4572329aa
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