qwen25-15b-biomed-finetuned – AI Model by yashm | AlphaNeural AI

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yashm/
qwen25-15b-biomed-finetuned

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text-generation

Qwen/Qwen2.5-1.5B

10.57967/hf/9362

text-generation-inference

endpoints_compatible

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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.

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

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

Example Usage

python

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"])

Training Details

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

Limitations

May hallucinate
Not medically validated
Limited to training data

Disclaimer

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

Author

Fine-tuned by Dr. YMG