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KETI-AIR
/
veld-base

Image-to-Text
Transformers
PyTorch
English
Korean
multilingual
veld
image-feature-extraction
vision, language
pretrained model
custom_code
Model card Files Files and versions
xet
Community
2

Instructions to use KETI-AIR/veld-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use KETI-AIR/veld-base 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="KETI-AIR/veld-base", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("KETI-AIR/veld-base", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
veld-base
1.36 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 10 commits
kimsan0622's picture
kimsan0622
Upload model
eb96320 over 3 years ago
  • .gitattributes
    1.43 kB
    initial commit over 3 years ago
  • README.md
    1.01 kB
    Add multilingual to the language tag (#1) over 3 years ago
  • config.json
    77.9 kB
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  • configuration_veld.py
    5.23 kB
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  • generation_config.json
    142 Bytes
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  • modeling_veld.py
    104 kB
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  • preprocessor_config.json
    437 Bytes
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  • processing_veld.py
    5.37 kB
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  • pytorch_model.bin
    1.35 GB
    xet
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  • special_tokens_map.json
    960 Bytes
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  • spiece.model
    1.59 MB
    xet
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  • tokenizer.json
    4.14 MB
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  • tokenizer_config.json
    1.52 kB
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