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dmis-lab
/
Gemma3-4B-CVRR

Visual Question Answering
Transformers
Safetensors
cvrr_merged
feature-extraction
cvrr
custom_code
latent-reasoning
Model card Files Files and versions
xet
Community

Instructions to use dmis-lab/Gemma3-4B-CVRR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use dmis-lab/Gemma3-4B-CVRR with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("visual-question-answering", model="dmis-lab/Gemma3-4B-CVRR", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("dmis-lab/Gemma3-4B-CVRR", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Gemma3-4B-CVRR / native_backbone
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  • 1 contributor
History: 1 commit
dmis-lab's picture
dmis-lab
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  • added_tokens.json
    35 Bytes
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  • chat_template.json
    1.62 kB
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  • config.json
    855 Bytes
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  • generation_config.json
    215 Bytes
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  • model.safetensors.index.json
    83.5 kB
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  • native-00001.safetensors
    4.9 GB
    xet
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  • native-00002.safetensors
    3.7 GB
    xet
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  • preprocessor_config.json
    570 Bytes
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  • processor_config.json
    70 Bytes
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  • special_tokens_map.json
    662 Bytes
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  • tokenizer.json
    33.4 MB
    xet
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  • tokenizer.model
    4.69 MB
    xet
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  • tokenizer_config.json
    1.16 MB
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