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Tonic
/
GemmaX2-28-2B-4bit

Translation
Transformers
Safetensors
gemma2
text-generation
gemma
multilingual
quantized
text-generation-inference
4-bit precision
bitsandbytes
Model card Files Files and versions
xet
Community

Instructions to use Tonic/GemmaX2-28-2B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Tonic/GemmaX2-28-2B-4bit 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="Tonic/GemmaX2-28-2B-4bit")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("Tonic/GemmaX2-28-2B-4bit")
    model = AutoModelForCausalLM.from_pretrained("Tonic/GemmaX2-28-2B-4bit")
  • Notebooks
  • Google Colab
  • Kaggle
GemmaX2-28-2B-4bit
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  • 1 contributor
History: 4 commits
Tonic's picture
Tonic
Update README.md
dab75ec verified over 1 year ago
  • .gitattributes
    1.57 kB
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  • README.md
    6.68 kB
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  • config.json
    1.35 kB
    Upload Gemma2ForCausalLM over 1 year ago
  • generation_config.json
    168 Bytes
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  • model.safetensors
    2.32 GB
    xet
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  • special_tokens_map.json
    555 Bytes
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  • tokenizer.json
    34.4 MB
    xet
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  • tokenizer_config.json
    46.8 kB
    Upload tokenizer over 1 year ago