JThomas-CoE/College-of-Experts-AI
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A framework decomposing large MoE models into disk-resident specialist networks for consumer hardware. Run SOTA-class ensembles locally on limited VRAM by dynamically loading experts. Proof of concept showed +27% benchmark gain over isolated models.
3 mentions on Hacker News by 1 person: 1 story, 2 comments · first 2026-03-11 · latest 2026-04-16
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…models (Q4_K_M GGUF, ~18B, Ollama-ready), histograms, masks, corpora and pipeline scripts: GitHub: https://github.com/JThomas-CoE/College-of-Experts-AI HF: https://huggingface.co/JThomas-CoE
comment by JThomas-CoE · 2026-04-16 · in Qwen3.5 50% expert reduction success -
…on consumer hardware (29GB VRAM footprint). Below are the relevant links: Whitepaper (PDF): [ https://github.com/JThomas-CoE/College-of-Experts-AI/blob/ma... ] The Extracted Models: [ https://huggingface.co/JThomas-CoE/CoE-WEB2-40b-A3b-GGUF…
comment by JThomas-CoE · 2026-03-11 · in Slicing an 80B MoE LLM into 40B domain specialists -
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Slicing an 80B MoE LLM into 40B domain specialistsstory by JThomas-CoE · 2026-03-11 · 1 comment