Galactica

Galactica

by Meta AI

Large language model trained on scientific literature for academic knowledge tasks

Open Source Artificial Superintelligence Python Hugging Face
Visit Product
66 upvotes 3,305 views

About

Galactica is a large language model trained exclusively on a massive corpus of scientific literature, textbooks, encyclopedias, and academic knowledge. Developed by Meta AI and released in November 2022, it was designed to store, combine, and reason about scientific knowledge — with the goal of helping scientists navigate and synthesize the exponentially growing body of academic research.

The model was trained on 48 million scientific papers, academic textbooks, scientific websites, encyclopedias, and reference materials. This specialized training made it unusually competent at scientific question answering, summarizing research papers, writing scientific content, and performing academic reasoning tasks compared to general-purpose LLMs trained on diverse web text.

Galactica was controversially taken offline just three days after its public demo in 2022 after demonstrations showed it confidently generating plausible-sounding but factually incorrect scientific text — a phenomenon that illustrated the fundamental challenge of AI hallucination in high-stakes domains. The model remains available for research use and continues to inform work on more reliable scientific AI systems.

Product Features

- Trained on 48 million scientific papers and textbooks
- Academic question answering and knowledge synthesis
- Scientific paper summarization
- Research literature navigation
- Math and equations understanding
- Multiple model sizes from 125M to 120B parameters
- Available on Hugging Face for research
- LaTeX equation generation
- Literature citation assistance
- Chemical formula and scientific notation support

About the Publisher

Galactica was developed by Meta AI in collaboration with Papers With Code. Meta AI (formerly FAIR) is one of the world's leading AI research organizations, contributing seminal work to deep learning, NLP, and computer vision. Galactica's reception and subsequent withdrawal highlighted important questions about AI reliability in scientific contexts that continue to shape how scientific AI tools are developed and evaluated.