article · Figshare · 2024

ALIGNN-BERT-TL codebase

Li, Youjia

Cited by 0Open access

Abstract

This repository contains the code for Hybrid-LLM-GNN transfer learning framework to predict materials properties using concatenated embeddings extracted from ALIGNN and BERT models. The code provides the following functions:Generate string representations of provided crystal samples using NLP tools: Robocystallographer and ChemNLPUse a pre-trained BERT/MatBERT langugae model to extract context-aware word embeddings from text descriptions of a given crystal structureConcatenate LLM embeddings with ALIGNN embeddings obtained from feature-extraction-based ALIGNNTLPost-analysis script for model performance analysis and text-based model explanation<br>

Cite this paper

APA 7

Li, Y. (2024). ALIGNN-BERT-TL codebase. Figshare. https://doi.org/10.6084/m9.figshare.27162276.v1

MLA 9

Li, Youjia. “ALIGNN-BERT-TL codebase.” Figshare, 2024, https://doi.org/10.6084/m9.figshare.27162276.v1.

Chicago

Li, Youjia. 2024. “ALIGNN-BERT-TL codebase.” Figshare. https://doi.org/10.6084/m9.figshare.27162276.v1.

Harvard

Li, Y. (2024) ‘ALIGNN-BERT-TL codebase’, Figshare. Available at: https://doi.org/10.6084/m9.figshare.27162276.v1.

BibTeX

@article{li2024alignn,
  title = {{ALIGNN-BERT-TL codebase}},
  author = {Li, Youjia},
  journal = {Figshare},
  year = {2024},
  doi = {10.6084/m9.figshare.27162276.v1}
}

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