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
- Xet hash:
- 3f91ee639f1e35d691bc1c80c423a6f1ca78894e98c6db9adff1387febce8d82
- Size of remote file:
- 11.4 MB
- SHA256:
- a695d235928a965851a35ca2350983f8079aec638c6d7a0cc0547a2860bdd67f
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