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shivavardhineedi
/
mini_internVL_eval

Feature Extraction
Transformers
Safetensors
internvl_chat
custom_code
Model card Files Files and versions
xet
Community

Instructions to use shivavardhineedi/mini_internVL_eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use shivavardhineedi/mini_internVL_eval with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="shivavardhineedi/mini_internVL_eval", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("shivavardhineedi/mini_internVL_eval", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
mini_internVL_eval
4.41 GB
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  • 1 contributor
History: 12 commits
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shivavardhineedi
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  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • config.json
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  • configuration_intern_vit.py
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  • configuration_internlm2.py
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  • configuration_internvl_chat.py
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  • conversation.py
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  • generation_config.json
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  • model.safetensors
    4.41 GB
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  • modeling_intern_vit.py
    18.2 kB
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  • modeling_internlm2.py
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  • modeling_internvl_chat.py
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  • special_tokens_map.json
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  • tokenization_internlm2.py
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  • tokenization_internlm2_fast.py
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  • tokenizer.model
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  • tokenizer_config.json
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