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---
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library_name: transformers
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license: apache-2.0
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datasets:
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- petkopetkov/medical-question-answering-synthetic
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base_model:
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- Qwen/Qwen2.5-0.5B-Instruct
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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---
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This model is a fintuned Qwen2.5-0.5B-Instruct on a custom preprocessed dataset (petkopetkov/medical-question-answering-synthetic). It was evaluated using qualitative ranking and achieves better results than the base model.
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### Usage
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First, install the Transformers library with:
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```sh
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pip install -U transformers
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```
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#### Run with the `pipeline` API
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```python
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from transformers import pipeline
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import torch
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system_prompt = (
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"You are a medical assistant trained to provide general health information. "
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"Follow these rules:\n"
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"1. Only answer the question asked.\n"
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"2. Do not provide any additional stories, anecdotes, or personal information.\n"
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"3. Do not deviate from medical facts.\n"
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"5. Do not include references/sources (papers, websites, etc.)\n"
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"6. Be concise and accurate.\n\n"
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""
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)
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prompt = "What is contact dermatitis, and what are some of the typical symptoms associated with this condition, including the type of hypersensitivity reaction that causes it?"
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chat = [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": prompt},
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]
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pipe = pipeline(
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task="text-generation",
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model="petkopetkov/Qwen2.5-0.5B-Instruct-med-diagnosis",
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torch_dtype=torch.bfloat16,
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device_map="auto",
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max_new_tokens=1024,
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)
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response = pipe(chat)
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print(response[0]["generated_text"][0])
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``` |
