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adirik/mamba-2.8b-slimpj

A large-scale implementation of the Mamba architecture featuring 2.8 billion parameters trained on the extensive SlimPajama dataset (600B tokens, double the token count of standard Mamba models). Mamba-2.8b-slimpj represents a significant advancement in performance compared to smaller variants, demonstrating competitive capabilities with similarly-sized transformer models while maintaining the architecture's inherent advantages in computational efficiency and scaling. The model excels at processing information-dense language data with exceptional context handling capabilities, making it particularly valuable for applications requiring advanced language understanding with efficient computational resource utilization.

Technical Specifications:

  • Architecture: Selective State Space Model (Mamba)
  • Parameters: 2.8 billion
  • Training Data: SlimPajama dataset (600B tokens)
  • Context Length: 2048 tokens
  • Computational Efficiency: 17% fewer FLOPs than comparable transformers
  • Hardware Compatibility: Nvidia L40S GPU
  • Applications: Advanced language processing, research, foundation for specialized models
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