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mlx-community
/
sarvam-translate-mlx-bf16

Translation
Transformers
Safetensors
MLX
gemma3
image-text-to-text
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use mlx-community/sarvam-translate-mlx-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mlx-community/sarvam-translate-mlx-bf16 with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "translation" 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("translation", model="mlx-community/sarvam-translate-mlx-bf16")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("mlx-community/sarvam-translate-mlx-bf16")
    model = AutoModelForMultimodalLM.from_pretrained("mlx-community/sarvam-translate-mlx-bf16", device_map="auto")
  • MLX

    How to use mlx-community/sarvam-translate-mlx-bf16 with MLX:

    # Download the model from the Hub
    pip install huggingface_hub[hf_xet]
    
    huggingface-cli download --local-dir sarvam-translate-mlx-bf16 mlx-community/sarvam-translate-mlx-bf16
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • LM Studio
  • Atomic Chat
sarvam-translate-mlx-bf16
9.14 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 14 commits
bibproj's picture
bibproj
Update README.md
3338ce9 verified about 1 year ago
  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • config.json
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  • model-00001-of-00002.safetensors
    5.34 GB
    xet
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  • model-00002-of-00002.safetensors
    3.77 GB
    xet
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  • model.safetensors.index.json
    45.8 kB
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  • special_tokens_map.json
    662 Bytes
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  • tokenizer.json
    33.4 MB
    xet
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  • tokenizer.model
    4.69 MB
    xet
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  • tokenizer_config.json
    1.16 MB
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