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dilr
/
Mira-Q2

Text Generation
PEFT
Safetensors
English
clinical
extraction
medical
qlora
lora
healthcare
on-prem
dilr
schema-agnostic
conversational
Model card Files Files and versions
xet
Community

Instructions to use dilr/Mira-Q2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use dilr/Mira-Q2 with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit")
    model = PeftModel.from_pretrained(base_model, "dilr/Mira-Q2")
  • Notebooks
  • Google Colab
  • Kaggle
Mira-Q2 / eval
749 kB
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  • 1 contributor
History: 2 commits
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shekharp77
Upload eval/training_metrics.json with huggingface_hub
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  • comprehensive_scorecard.json
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  • extraction_relevant_150_partial.jsonl
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  • extraction_relevant_150_result.json
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  • mtsamples_282_partial.jsonl
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  • mtsamples_282_result.json
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  • synthetic_v2_150_partial.jsonl
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  • synthetic_v2_150_result.json
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  • test_gold_200_partial.jsonl
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  • test_gold_200_result.json
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  • training_metrics.json
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