nach0: multimodal natural and chemical languages foundation model.
Chem Sci
; 15(22): 8380-8389, 2024 Jun 05.
Article
en En
| MEDLINE
| ID: mdl-38846388
ABSTRACT
Large Language Models (LLMs) have substantially driven scientific progress in various domains, and many papers have demonstrated their ability to tackle complex problems with creative solutions. Our paper introduces a new foundation model, nach0, capable of solving various chemical and biological tasks biomedical question answering, named entity recognition, molecular generation, molecular synthesis, attributes prediction, and others. nach0 is a multi-domain and multi-task encoder-decoder LLM pre-trained on unlabeled text from scientific literature, patents, and molecule strings to incorporate a range of chemical and linguistic knowledge. We employed instruction tuning, where specific task-related instructions are utilized to fine-tune nach0 for the final set of tasks. To train nach0 effectively, we leverage the NeMo framework, enabling efficient parallel optimization of both base and large model versions. Extensive experiments demonstrate that our model outperforms state-of-the-art baselines on single-domain and cross-domain tasks. Furthermore, it can generate high-quality outputs in molecular and textual formats, showcasing its effectiveness in multi-domain setups.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Chem Sci
Año:
2024
Tipo del documento:
Article
Pais de publicación:
Reino Unido