el4/VeriLoop-E2-Dflash2-experimental

This is an experimental research artifact, it does actually run but I can't verify acceptance rates because my 12gb of vram apparently doesnt cut it because kv caches and all that

But yeah it does work- this was trained on a laptop gpu which is kinda crazy ngl

if you want to try it- use ik_llama.cpp

heres the self eval:

python -m toffee xspark eval --head xspark_out/dflash2/dflash2_head.pt \
          --target-model ./VeriLoop-E2 --data-dir xspark_data/harvest --anchors 512
{"name": "NVIDIA GeForce RTX 4080 Laptop GPU", "vram_gb": 11.67608642578125, "event": "gpu_detected", "level": "info", "timestamp": "2026-11-06T14:22:03.355667Z"}
{
  "variant": "dflash2",
  "n_blocks": 512,
  "block_size": 8,
  "accept_len": 1.171875,
  "oracle_len": 2.068359375,
  "accept@0": 0.15625,
  "recall@0": 0.49609375,
  "accept@1": 0.015625,
  "recall@1": 0.26171875,
  "accept@2": 0.0,
  "recall@2": 0.13671875,
  "accept@3": 0.0,
  "recall@3": 0.078125,
  "accept@4": 0.0,
  "recall@4": 0.048828125,
  "accept@5": 0.0,
  "recall@5": 0.029296875,
  "accept@6": 0.0,
  "recall@6": 0.017578125
} 

What the numbas say:

metric	value	plain english
recall@0	254/512 = 49.6%	the true next token is in your top-16 half the time — the head knows it
accept@0	80/512 = 15.6%	the walk picks it 16% of the time
gap	174 anchors	truth was sitting in the candidate list and the selector walked past it
oracle_len	2.068	accept length if the walk always picked the truth when available — the ceiling of this head as-is
accept_len	1.172	you're capturing (1.17−1)/(2.07−1) ≈ 16% of the available headroom

if you want to recreate this abomination use my llm toolkit