Image-Text-to-Text
PEFT
Safetensors
English
lora
qwen2.5-vl
vision-language-model
medical
medical-vqa
chain-of-thought
reasoning
grpo
trl
conversational
Instructions to use researcher2026/OpenMedReason with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use researcher2026/OpenMedReason with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-VL-7B-Instruct") model = PeftModel.from_pretrained(base_model, "researcher2026/OpenMedReason") - Notebooks
- Google Colab
- Kaggle
metadata
base_model: unsloth/Qwen2.5-VL-7B-Instruct
library_name: peft
pipeline_tag: image-text-to-text
license: apache-2.0
language:
- en
datasets:
- researcher2026/OpenMedReason
tags:
- peft
- lora
- qwen2.5-vl
- vision-language-model
- medical
- medical-vqa
- chain-of-thought
- reasoning
- grpo
- trl
- base_model:adapter:unsloth/Qwen2.5-VL-7B-Instruct
model-index:
- name: OpenMedReason-Qwen2.5-VL-7B-GRPO-LoRA
results: []