mechramc/kalavai-phase1-1b-code-specialist-seed42
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KALAVAI — Code Specialist (pythia-1b, seed 42)
Fine-tuned EleutherAI/pythia-1b on Code data as part of the KALAVAI decentralized cooperative training protocol.
- Paper: KALAVAI: Predicting When Independent Specialist Fusion Works -- A Quantitative Model for Post-Hoc Cooperative LLM Training
- GitHub: https://github.com/mechramc/Kalavai
Paper results
Phase 1 English domains at 1B scale. MoE fusion: +7.49% ±0.01pp over best specialist (3 seeds). Mean divergence 15.28%.
How to use
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("mechramc/kalavai-phase1-1b-code-specialist-seed42")
tokenizer = AutoTokenizer.from_pretrained("EleutherAI/pythia-1b")This model is one specialist in a KALAVAI cooperative. To reproduce the MoE fusion results from the paper, load multiple domain specialists and combine them with a trained MoE router (see the paper and GitHub for details).
Citation
@article{kumaresan2026kalavai,
title = {{KALAVAI}: Predicting When Independent Specialist Fusion Works
--- A Quantitative Model for Post-Hoc Cooperative {LLM} Training},
author = {Kumaresan, Ramchand},
journal = {arXiv preprint arXiv:2603.22755},
year = {2026},
url = {https://arxiv.org/abs/2603.22755}
}