Holo LLM — HRR Attention Conversions

Archive / conversion-track repo. Drop-in HRR attention experiments on Qwen2.5 (swap softmax for a fixed-size holographic state).

Live Status (2026-08-13)

The conversion-track table below is historical. Those “converting / queued / QLoRA” rows are not live jobs. Do not treat this card as the product.

Current product / live jobs (other repos / boxes):

What Where
DeepSeek-V4-Flash in-weight HRR overlay (memory 5/5 vs 0/5, KV spill needle) staccs/lecore-deepseek-v4-flash-hrr
Qwen3.5-9B Unicron assimilate prove staccs/lecore-qwen35-9b-assimilated
GPT-2 HRR vs softmax code + small ckpts staccs/lecore-hrr-gpt2
Qwen3.5-397B Galvatron Vast 47593358 — not uploaded
OLMo 2 from-scratch HRR (original mix) Vast 47603357 8×A100 — no loss yet, not this repo

Historical conversion track (stale)

Model Status as originally written
Qwen2.5-0.5B-Instruct → HRR Converted, fine-tuning (old)
Qwen2.5-7B-Instruct → HRR Converting (old)
Qwen2.5-14B-Instruct → HRR Queued (old)
Qwen2.5-32B-Instruct → HRR QLoRA fine-tuning (old)
Qwen2.5-72B-Instruct → HRR Queued (old)

This repo still holds conversion scripts and some Qwen2.5-1.5B / gated-scan checkpoints. That is the artifact. It is not a hosted 72B.

How it was supposed to work

Each attention module is replaced with HRR attention — a gated holographic recurrence that stores context in a fixed-size superposed state. Conversion copies Q/K/V/O projection weights and adds learned per-frequency forgetting gates.

from transformers import AutoModelForCausalLM, AutoTokenizer
# only if the subfolder actually exists in this repo
model = AutoModelForCausalLM.from_pretrained("staccs/holo-llm-hrr-attention", subfolder="qwen0.5b_hrr")

See also

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