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rediska0123
/
gemma29bit-sciqa-lora-correctness-2epochs

Feature Extraction
Transformers
Safetensors
qwen2
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use rediska0123/gemma29bit-sciqa-lora-correctness-2epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use rediska0123/gemma29bit-sciqa-lora-correctness-2epochs with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="rediska0123/gemma29bit-sciqa-lora-correctness-2epochs", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("rediska0123/gemma29bit-sciqa-lora-correctness-2epochs", trust_remote_code=True)
    model = AutoModel.from_pretrained("rediska0123/gemma29bit-sciqa-lora-correctness-2epochs", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
gemma29bit-sciqa-lora-correctness-2epochs
14.2 GB
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  • 1 contributor
History: 6 commits
rediska0123's picture
rediska0123
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9f5b463 verified 2 months ago
  • .gitattributes
    1.57 kB
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  • README.md
    5.17 kB
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  • added_tokens.json
    193 Bytes
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  • chat_template.jinja
    395 Bytes
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  • config.json
    827 Bytes
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  • configuration_qwen2_rm.py
    6.69 kB
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  • merges.txt
    1.67 MB
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  • model-00001-of-00003.safetensors
    4.88 GB
    xet
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  • model-00002-of-00003.safetensors
    4.93 GB
    xet
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  • model-00003-of-00003.safetensors
    4.36 GB
    xet
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  • model.safetensors.index.json
    28 kB
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  • modeling_qwen2_rm.py
    74.7 kB
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  • special_tokens_map.json
    444 Bytes
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  • tokenizer.json
    11.4 MB
    xet
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  • tokenizer_config.json
    2.08 kB
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  • vocab.json
    2.78 MB
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