architkaila / Fine-Tuning-LLMs-for-Medical-Entity-ExtractionLinks
Exploring the potential of fine-tuning Large Language Models (LLMs) like Llama2 and StableLM for medical entity extraction. This project focuses on adapting these models using PEFT, Adapter V2, and LoRA techniques to efficiently and accurately extract drug names and adverse side-effects from pharmaceutical texts
☆79Updated last year
Alternatives and similar repositories for Fine-Tuning-LLMs-for-Medical-Entity-Extraction
Users that are interested in Fine-Tuning-LLMs-for-Medical-Entity-Extraction are comparing it to the libraries listed below
Sorting:
- A large-scale (194k), Multiple-Choice Question Answering (MCQA) dataset designed to address realworld medical entrance exam questions.☆221Updated 2 years ago
- Integrating knowledge graphs (KG) with large language models (LLM)