SpikingBrain-7B: Brain-Inspired Large Language Model with Hybrid Architecture
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Summary
SpikingBrain-7B is a brain-inspired large language model that integrates hybrid efficient attention, MoE (Mixture of Experts) modules, and spike encoding into its architecture. It features a universal conversion pipeline compatible with open-source models, enabling continual pre-training with less than 2% of data while achieving performance comparable to mainstream open-source models. The project includes technical reports in both Chinese and English, is available on arXiv, and provides accessible models for development.
Key quotes
· 3 pulledInspired by brain mechanisms, SpikingBrain integrates hybrid efficient attention, MoE modules, and spike encoding into its architecture
supported by a universal conversion pipeline compatible with the open-source model ecosystem
enables continual pre-training with less than 2% of the data while achieving performance comparable to mainstream open-source models
Contribute to BICLab/SpikingBrain-7B development by creating an account on GitHub.
