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ybelkada
/
blip2-opt-2.7b-fp16-sharded

Visual Question Answering
Transformers
PyTorch
blip-2
Model card Files Files and versions
xet
Community
2

Instructions to use ybelkada/blip2-opt-2.7b-fp16-sharded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ybelkada/blip2-opt-2.7b-fp16-sharded with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("visual-question-answering", model="ybelkada/blip2-opt-2.7b-fp16-sharded")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering
    
    processor = AutoProcessor.from_pretrained("ybelkada/blip2-opt-2.7b-fp16-sharded")
    model = AutoModelForVisualQuestionAnswering.from_pretrained("ybelkada/blip2-opt-2.7b-fp16-sharded")
  • Notebooks
  • Google Colab
  • Kaggle

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Collection including ybelkada/blip2-opt-2.7b-fp16-sharded

Sharded checkpoints

Collection
useful sharded checkpoints for users to run inference / fine-tuning on a Google colab without having to deal with CPU OOM issues. β€’ 7 items β€’ Updated Dec 9, 2023 β€’ 4
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