Video-Text-to-Text
Transformers
Safetensors
English
llava
text-generation
multimodal
vision-language
video understanding
spatial reasoning
visuospatial cognition
qwen
llava-video
Eval Results (legacy)
Instructions to use nkkbr/ViCA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkkbr/ViCA with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("nkkbr/ViCA") model = AutoModelForCausalLM.from_pretrained("nkkbr/ViCA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec79decff4231e2cab231f793f30f0a70855f9ac16313ebfb1f1e90fda6cedb0
- Size of remote file:
- 8.06 kB
- SHA256:
- bc9ae3ea0587354614e36e0f15bb76e2ccae037ac71c0a61be92bf2d2e71e301
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