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nkkbr
/
ViCA-ScanNet

Video-Text-to-Text
Transformers
Safetensors
English
llava
text-generation
multimodal
vision-language
video understanding
spatial reasoning
visuospatial cognition
qwen
llava-video
Model card Files Files and versions
xet

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
ViCA-ScanNet
16.1 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
nkkbr's picture
nkkbr
Update README.md
a94043e verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    612 Bytes
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  • added_tokens.json
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  • config.json
    3.52 kB
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  • generation_config.json
    243 Bytes
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  • merges.txt
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  • model-00001-of-00004.safetensors
    4.88 GB
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  • model-00002-of-00004.safetensors
    4.93 GB
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  • model-00003-of-00004.safetensors
    4.99 GB
    xet
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  • model-00004-of-00004.safetensors
    1.26 GB
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  • model.safetensors.index.json
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  • special_tokens_map.json
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  • tokenizer.json
    7.03 MB
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  • tokenizer_config.json
    1.54 kB
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  • trainer_state.json
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  • training_args.bin
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  • vocab.json
    2.78 MB
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