LoRA weights for Llama-2 NERRE

Low rank adaptation fine-tuned weights for Llama 2 experiments for simultaneously extracting named entities and their relationships in structured format, with results shown in the paper "*Structured information extraction from scientific text with large language models*" in Nature Communications by John Dagdelen*, Alexander Dunn*, Sanghoon Lee, Nicholas Walker, Andrew S. Rosen, Gerbrand Ceder, Kristin Persson, and Anubhav Jain.
Includes 13 independent experiments for three different tasks:
General materials information extraction (five cross validation folds, one fine-tune model for each)Metal organic frameworks information extraction (five cross validation folds, one fine-tune model for each)Inorganic impurity doping information extraction (one test set for each of three schemas - JSON, English, and ExtraEnglish, each corresponding to one model)