Video-Text-to-Text
Transformers
Safetensors
English
llava
text-generation
multimodal
vision-language
video understanding
spatial reasoning
visuospatial cognition
qwen
llava-video
Instructions to use nkkbr/ViCA-ScanNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkkbr/ViCA-ScanNet with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("nkkbr/ViCA-ScanNet") model = AutoModelForCausalLM.from_pretrained("nkkbr/ViCA-ScanNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 163d370d1f497d717ae31c1953ae3aee91a441dd2682a7b856915ae94dae9a5b
- Size of remote file:
- 8.06 kB
- SHA256:
- e6b4aa33f55e48e79da409167c0502ab30cbbfa7d18bea5b24f75297f9188653
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