A medical-domain adaptation of Mistral-7B-Instruct-v0.2, fine-tuned using Parameter-Efficient Fine-Tuning (PEFT) with LoRA for medical question answering and healthcare AI research. > Important: This model is intended for research, experimentation, and educational use only. It has not been clinically validated and must not be used as a substitute for professional medical advice, diagnosis, treatment, or clinical decision-making. This model is a domain-adapted version of mistralai/Mistral-7B-Instruct-v0.2. Rather than training a foundation model from scratch, this project applies Low-Rank Adaptation (LoRA) using the Hugging Face PEFT framework to specialize Mistral-7B-Instruct-v0.2 for medical question-answering tasks. — Developer: Ansh Punia — Project type: Independent AI/ML research and engineering project — Model type: PEFT/LoRA adapter for a decoder-only causal language model — Base model: mistralai/Mistral-7B-Instruct-v0.2 — Base model size: Approximately 7 billion parameters — Fine-tuning method: Low-Rank Adaptation (LoRA) — Framework: Hugging Face Transformers + PEFT — Primary task: Medical-domain question answering and text generation — Language: Primarily English -…
Модальности:
Генерация текста
Области применения:
Диалог / чат Ответы на вопросы Медицина
Задача: Генерация текста
Автор: anshpunia8597
Теги: peft, tensorboard, lora, medical, medical-qa, healthcare, question-answering, research
Лайков: 3 | Загрузок: 26
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
