Text Generation
PEFT
Safetensors
English
radiology
medical
healthcare
clinical-nlp
qwen
impression-generation
lora
4bit
conversational
Instructions to use Medico/Qwen3.8-27B-Radiology-Impression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Medico/Qwen3.8-27B-Radiology-Impression with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.8-27B") model = PeftModel.from_pretrained(base_model, "Medico/Qwen3.8-27B-Radiology-Impression") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- README.md +10 -4
- adapter_config.json +4 -4
- adapter_model.safetensors +1 -1
README.md
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- 4bit
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pipeline_tag: text-generation
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widget:
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- text:
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---
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# 🩻 Qwen 3.8-27B Clinical Radiology Impression & Consultation AI
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pipeline_tag: text-generation
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widget:
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- text: '[EXAM: CT CHEST]
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FINDINGS: Large saddle pulmonary embolus with right ventricular dilation (RV/LV
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ratio 1.4).'
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example_title: CT Pulmonary Embolism
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- text: '[EXAM: MRI BRAIN]
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FINDINGS: Restricted diffusion in left MCA territory with abrupt flow truncation
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at M1 bifurcation.'
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example_title: Brain MRI Stroke
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---
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# 🩻 Qwen 3.8-27B Clinical Radiology Impression & Consultation AI
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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"down_proj",
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"up_proj",
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"k_proj",
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"gate_proj",
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"o_proj",
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"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"up_proj",
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"gate_proj",
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"o_proj",
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"q_proj",
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"v_proj",
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"down_proj",
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"k_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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