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potteryrage/
aileron-0.8-laminar-student-v1

Name: aileron-0.8-laminar-student-v1
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Aileron 0.8 Laminar Student v1

This is a custom Laminar-native sparse student checkpoint distilled from Qwen/Qwen3.5-0.8B.

It is not a standard Hugging Face AutoModelForCausalLM checkpoint. The artifact contains the sparse student modules used to patch selected Qwen decoder MLPs at runtime:

learned residency-constrained router
page-local SwiGLU experts
cache-resident correction path
trainable final-head bias/scale

Files

laminar_student.pt - trained sparse student checkpoint.
training_config.json - full Modal training config.
metadata.json - run metadata.
laminar_student_metrics.csv - training metrics.
eval_summary.json - final evaluation summary.
eval_rollouts.csv - final rollout outputs and gate metrics.
aileron_train_laminar_student.py - trainer used for this artifact.
aileron_eval_laminar_student.py - evaluator used for the final gate.

Training Run

GPU: Modal B200
Steps: 20,000
Sequence length: 128
Sparse layers: 0,1,2
AP/pages/expert hidden: AP32, 256 pages, H32
Correction rank: 16
Wall time: about 1h53m

Required Decoding Policy

The checkpoint passed the basic 256-token chat gate with:

json

{
  "repetition_penalty": 1.08,
  "no_repeat_ngram_size": 4,
  "temperature": 0.0
}

Do not evaluate this artifact with unconstrained greedy decoding; the raw greedy run still showed long-horizon repetition. The decoding policy above is part of the functional artifact contract.

Final Gate Summary

eval_summary.json:

passed_basic_chat_gate: true
max_repeated_4gram_rate_256: 0.0
max_line_repeat_256: 1
story_contamination: false
malformed_fragment: false

This is a functional Laminar sparse-student checkpoint for continued runtime and MLX/Laminar integration work, not a general-purpose replacement for the dense Qwen teacher.

potteryrage/aileron-0.8-laminar-student-v1