library_name, tags, license, base_model

library_name	tags	license	base_model
transformers	qwen biomedical bioinformatics fine-tuned medical llm	apache-2.0	Qwen/Qwen2.5-1.5B

Qwen2.5-1.5B Biomedical Fine-Tuned Model

This model is a biomedical and bioinformatics fine-tuned version of Qwen/Qwen2.5-1.5B, fine-tuned by Dr. YMG.

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Model Details

Model Description

This model is a domain-adapted and instruction fine-tuned large language model specialized for biomedical and bioinformatics tasks.

• Developed by: Dr. YMG
• Model type: Causal Language Model (LLM)
• Language(s): English
• License: Apache 2.0
• Finetuned from model: Qwen/Qwen2.5-1.5B

Model Sources

• Repository: https://huggingface.co/yashm/qwen25-15b-biomed-finetuned
• Base Model: https://huggingface.co/Qwen/Qwen2.5-1.5B

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Uses

Direct Use

• Biomedical concept explanation
• Bioinformatics discussions
• Research assistance
• Literature summarization
• Gene expression & biomarker discussion

Out-of-Scope Use

• Clinical diagnosis
• Medical treatment decisions
• Drug prescription
• Patient-specific advice

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Example Usage

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
import torch

MODEL_ID = "yashm/qwen25-15b-biomed-finetuned"

tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_ID,
    device_map="auto",
    dtype=torch.bfloat16,
    trust_remote_code=True,
)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Explain gene expression in simple terms."

out = pipe(prompt, max_new_tokens=200)
print(out[0]["generated_text"])

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Training Details

• Base model: Qwen/Qwen2.5-1.5B
• Method: LoRA (PEFT)
• Precision: BF16
• Quantization: 4-bit QLoRA

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Limitations

• May hallucinate
• Not medically validated
• Limited to training data

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Disclaimer

For research and educational use only. Not for clinical decision-making.

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Author

Fine-tuned by Dr. YMG