https://huggingface.co/datasets/FreedomIntelligence/medical-o1-reasoning-SFT
A Hugging Face dataset is trending named "medical-o1-reasoning-SFT", created by Freedom Intelligence.
Overview:
This dataset is intended for fine-tuning language models to perform better on medical reasoning tasks. Specifically, it's designed for instruction-following and medical reasoning tasks involving step-by-step logic and clinical decision-making scenarios.
Key Characteristics:
- Domain: Medical (Healthcare, Clinical Reasoning, and Diagnostics)
- Task Type: Supervised Fine-Tuning (SFT), Instruction-based, Chain-of-thought reasoning.
- Purpose: Enhancing language models' abilities in medical reasoning, clinical decision-making, and improving their logical explanations and step-by-step reasoning.
Ideal Use Cases:
- Developing medical assistant AIs capable of performing diagnostic reasoning.
- Training models on medically accurate, instruction-following behaviors.
- Improving AI explainability for clinical decision-making scenarios.