Spiking-CODER v2 🧠⚑

Spiking-CODER v2 is an improved fine-tuned LLM for SNN programming, trained on a hybrid dataset that emphasizes human-written code.


πŸ“Š Training Data

  • Hybrid-v2 Dataset:
    • 40K raw SNN code samples from GitHub.
    • Dataset heavily features Brian2 code, with additional coverage of snnTorch and Norse.
    • Prompts: Synthetic, generated by Mistral-Large.
    • Outputs: Always human-written SNN code.

🎯 Key Features

  • More realistic training distribution by keeping outputs strictly human-authored.
  • Training objective focused on minimizing runtime errors and improving functional pass rates.
  • Better alignment with runnable examples across SNN Frameworks (Brian2, snnTorch, Norse, etc.).
  • Higher composite evaluation score and Functional Pass rates on SNNBench compared to v1.

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