eagle3-new-model

name	eagle3-new-model
description	Add a new model to the EAGLE3 offline pipeline. Generates an hf_offline_eagle3.yaml launcher config for a new model checkpoint, choosing the right hidden state dump backend (TRT-LLM / HF / vLLM) and GPU configuration. Use when user wants to run EAGLE3 on a model that does not yet have a YAML in tools/launcher/examples/ or asks how to configure the pipeline for a new checkpoint.
user_invocable	true

EAGLE3 New Model Configuration

Create tools/launcher/examples/<Org>/<Model>/hf_offline_eagle3.yaml by copying the closest existing example and adapting it. Pick a reference with the same shape as the target (dense vs MoE, similar size) from tools/launcher/examples/ — e.g. the Qwen3-8B config for a dense model.

The pipeline is a 4-task config (task_0 data synthesis → task_1 hidden-state dump → task_2 train → task_3 benchmark). The task structure, args, containers, and GPU/node sizing are all visible in the existing examples — infer them from a reference rather than hand-rolling. This file documents only the two things that are not obvious from the examples: which dump backend to pick, and the model-specific gotchas.

Choosing the task_1 hidden-state dump backend

Backend	Script	When to use
vLLM	common/eagle3/dump_offline_data_vllm.sh	Default. Broad coverage via vLLM's native hidden-state extractor.