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CUDAOUTOFMEMORY
/
PLUME-Qwen2-VL-2B

Feature Extraction
Transformers
Safetensors
English
qwen2_vl
image-text-to-text
Model card Files Files and versions
xet
Community
1

Instructions to use CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B")
    model = AutoModelForImageTextToText.from_pretrained("CUDAOUTOFMEMORY/PLUME-Qwen2-VL-2B")
  • Notebooks
  • Google Colab
  • Kaggle
PLUME-Qwen2-VL-2B
4.52 GB
Ctrl+K
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  • 2 contributors
History: 7 commits
CUDAOUTOFMEMORY's picture
CUDAOUTOFMEMORY
nielsr's picture
nielsr HF Staff
Add metadata and improve model card (#1)
6cf1262 about 2 months ago
  • .gitattributes
    1.52 kB
    initial commit about 2 months ago
  • README.md
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  • added_tokens.json
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  • chat_template.json
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  • config.json
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  • generation_config.json
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  • merges.txt
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  • model.safetensors
    4.51 GB
    xet
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  • preprocessor_config.json
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  • special_tokens_map.json
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  • tokenizer_config.json
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  • trainer_state.json
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  • vocab.json
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