eagle3-triage

Installation
SKILL.md

EAGLE3 Pipeline Triage

Diagnose failures in the 4-step EAGLE3 offline pipeline. This skill walks through each step, identifies the failure point, and provides actionable fixes.

Pipeline Overview

Step Script Purpose Common failure area
task_0 common/vllm/query.sh Data synthesis via vLLM server Server startup, model loading, OOM
task_1 common/eagle3/dump_offline_data_vllm.sh (or _hf.sh / .sh) Dump hidden states Backend selection, OOM, unsupported arch
task_2 common/eagle3/train_eagle.sh Train EAGLE3 draft head Dependencies, training crash, export
task_3 common/specdec_bench/quick_check.sh Benchmark acceptance rate Engine startup, draft model loading

Step 0 — Locate the experiment

Ask the user for one of:

  • Experiment directory (e.g., the --job-dir passed to launch.py or slurm.py)
  • The model name / YAML they ran
Installs
2
GitHub Stars
3.3K
First Seen
Jul 6, 2026
eagle3-triage — nvidia/model-optimizer