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mlx-community
/
GLM-OCR-8bit

Image-to-Text
Transformers
Safetensors
MLX
glm_ocr
image-text-to-text
8-bit precision
Model card Files Files and versions
xet
Community

Instructions to use mlx-community/GLM-OCR-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mlx-community/GLM-OCR-8bit 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="mlx-community/GLM-OCR-8bit")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("mlx-community/GLM-OCR-8bit")
    model = AutoModelForImageTextToText.from_pretrained("mlx-community/GLM-OCR-8bit")
  • MLX

    How to use mlx-community/GLM-OCR-8bit with MLX:

    # Download the model from the Hub
    pip install huggingface_hub[hf_xet]
    
    huggingface-cli download --local-dir GLM-OCR-8bit mlx-community/GLM-OCR-8bit
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • LM Studio
GLM-OCR-8bit
1.59 GB
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  • 1 contributor
History: 2 commits
prince-canuma's picture
prince-canuma
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350a346 verified 3 months ago
  • .gitattributes
    1.52 kB
    initial commit 3 months ago
  • README.md
    592 Bytes
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  • chat_template.jinja
    4.61 kB
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  • config.json
    2.08 kB
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  • generation_config.json
    165 Bytes
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  • model.safetensors
    1.58 GB
    xet
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  • model.safetensors.index.json
    56 kB
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  • preprocessor_config.json
    367 Bytes
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  • processor_config.json
    597 Bytes
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  • tokenizer.json
    6.84 MB
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  • tokenizer_config.json
    1.07 kB
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