OLMo2-1B EEG Code Generator (v8)

A 1.3B parameter language model fine-tuned for EEG/LFP neuroscience code generation, specializing in Parkinson's disease research.

Model Description

Built at the Neural Dynamics and Modulation Lab (NDML), Cleveland Clinic. Trained using OLMo-Core on a mixed web + code corpus, then fine-tuned on synthetic EEG analysis examples covering MNE-Python, EEGlab, FieldTrip, and Chronux.

Base model: OLMo2-1B (mixed web + Python + MATLAB pretraining) Fine-tuning: 8 iterations on EEG toolbox code generation pairs Best benchmark score: 0.937 (30/30 prompts passing)

Capabilities

MNE-Python EEG preprocessing and analysis
Beta band oscillation analysis for Parkinson's disease
LFP analysis from DBS lead recordings
FieldTrip, EEGlab, and Chronux MATLAB toolbox code
GPi/STN local field potential analysis
Closed-loop DBS (eiDBS) analysis pipelines

Usage

Training Details

Parameters: 1.3B
Pretraining: 868M web tokens (Dolma v1.7) + 654M mixed web/code tokens
Fine-tuning data: ~3,200 synthetic Claude-generated EEG code pairs
Hardware: NVIDIA A100 80GB PCIe
Framework: OLMo-Core v1.9.0

Lab

Neural Dynamics and Modulation Laboratory
Cleveland Clinic Lerner Research Institute
PI: David Escobar Sanabria, PhD

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