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mo-thecreator
/
ViT-GPT2-Image_Captioning_model

Image-to-Text
Transformers
Safetensors
vision-encoder-decoder
image-text-to-text
Generated from Trainer
image-captioning
Model card Files Files and versions
xet
Community

Instructions to use mo-thecreator/ViT-GPT2-Image_Captioning_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mo-thecreator/ViT-GPT2-Image_Captioning_model with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("image-to-text", model="mo-thecreator/ViT-GPT2-Image_Captioning_model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("mo-thecreator/ViT-GPT2-Image_Captioning_model")
    model = AutoModelForImageTextToText.from_pretrained("mo-thecreator/ViT-GPT2-Image_Captioning_model")
  • Notebooks
  • Google Colab
  • Kaggle
ViT-GPT2-Image_Captioning_model
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  • 1 contributor
History: 4 commits
Mohammed Abdeldayem
Update preprocessor_config.json
cb6dbf1 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    1.57 kB
    Upload README.md over 1 year ago
  • config.json
    4.86 kB
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  • generation_config.json
    89 Bytes
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  • merges.txt
    456 kB
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  • model.safetensors
    957 MB
    xet
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  • preprocessor_config.json
    329 Bytes
    Update preprocessor_config.json over 1 year ago
  • special_tokens_map.json
    131 Bytes
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  • tokenizer.json
    2.11 MB
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  • tokenizer_config.json
    476 Bytes
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  • training_args.bin
    5.3 kB
    xet
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  • vocab.json
    798 kB
    Upload ViT-GPT2 model over 1 year ago