InternLM Open-Sources Sage-SciPerception (ShuSheng·YuanZheng): Connecting Scientific Encoders to Language Models
GitHub - InternLM/Sage-SciPerception · GitHub
InternLM has open-sourced Sage-SciPerception (ShuSheng·YuanZheng), which maps scientific encoders such as molecular graphs, spectra, crystal structures, protein and nucleic acid sequences into the language model input space through a trainable projector, and trains them separately by task. On QM9S joint spectral-structure recognition, Acc@1 is 49.75%; on BEACON ncRNA family classification, accuracy is 97.35%; and on JARVIS-DFT formation energy prediction, MAD/MAE is 15.03. The project provides three demos, and the projector checkpoint will be released on Hugging Face.
Body
BranchesTagsOpen more actions menu
NameNameLast commit messageLast commit date
Repository files navigation
Sage-SciPerception
Sage Sci Perception · 书生·元征
Scientific perception for language models.
English · 简体中文
🤗 Models · GitHub · Demos · Results
Introduction
Sage Sci Perception (书生·元征) connects scientific encoders to a language model through trainable projectors. It maps molecular graphs, spectra, crystal structures, protein and nucleic-acid sequences, and scientific signals into the language model's input space, enabling natural-language analysis and structured scientific answers. Projectors are trained for each task.
Framework
Demos
Three spectra → molecular structure
IR, Raman and UV–Vis with streamed analysis and a recorded prediction.
Protein interface sites
Sequence positions and reference residue-level annotations.
Crystal structure and formation energy
Atomic geometry and a reference material property.
RNA interface refinement
Design revisions guided by experimental feedback.
Results
Selected results from task-specific checkpoints, evaluated on generated answers.
Benchmark Task Metric ↑ Score
QM9S Joint-spectrum structure identification Acc@1 (%) 49.75
JARVIS-DFT Formation-energy prediction MAD/MAE 15.03
MPBind, assembly-1 reconstruction PPI interface sites Mean per-protein F1 (%) 61.12
SciTS PHU01 ECG classification Macro-F1 (%) 71.53
SciTS NEU06 Sleep staging Macro-F1 (%) 72.01
BEACON ncRNA RNA family classification Accuracy (%) 97.35
Projector checkpoints will be available on Hugging Face.
AboutNo description, website, or topics provided.
ResourcesReadmeActivityCustom properties
Stars0 stars
Watchers0 watching
Forks0 forksReport repository