Video-Text-to-Text
Transformers
Safetensors
English
qwen3_5
text-generation
video
multimodal
video-captioning
temporal-grounding
qwen
VLM
custom_code
Instructions to use cudabenchmarktest/video-scan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cudabenchmarktest/video-scan with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("cudabenchmarktest/video-scan", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("cudabenchmarktest/video-scan", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "size": { | |
| "longest_edge": 16777216, | |
| "shortest_edge": 65536 | |
| }, | |
| "patch_size": 16, | |
| "temporal_patch_size": 2, | |
| "merge_size": 2, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "processor_class": "Qwen3VLProcessor", | |
| "image_processor_type": "Qwen2VLImageProcessorFast" | |
| } |