OptGuide Target 62: Proofreader API

What It Is

Target 62 (OPTIMIZATION_TARGET_MODEL_EXECUTION_FEATURE_PROOFREADER_API) is the configuration and fine-tuning weights for Chrome's on-device Proofreader API, powered by Gemini Nano.

Unlike most config-only targets, this one ships 16.6 MB of LoRA adaptation weights that specialize the base model for grammar correction.

Files

File	Size	Role
`model-info.pb`	198 B	Metadata: base model = `v3Nano`, version `2025.06.30.1229`
`on_device_model_execution_config.pb`	1.6 KB	System prompts for proofreading and error classification
`adaptation_weights.bin`	16.6 MB	LoRA weights to fine-tune Gemini Nano for proofreading
`model.tflite`	0 B	Empty placeholder (uses shared base model)

What It Does

Two tasks:

1. Proofreading (correct text)

System prompt: "You are a skilled proofreader that can identify and correct grammatical errors in a given text in the GIVEN_TEXT section. Your task is to proofread the GIVEN_TEXT and output the PROOFREAD_TEXT. Output ONLY the PROOFREAD_TEXT and nothing else."

2. Error Classification (label corrections)

System prompt: "You are a skilled proofreading teacher that correctly labels the correction made to the ORIGINAL_TEXT for proofreading."

Labels a correction as one of: Spelling, Punctuation, Capitalization, Preposition, Missing words, Grammar

Output format: {"label": "<label>"}

How It Works

A web page or Chrome feature calls the Proofreader API
Chrome loads this config and the LoRA adaptation weights
The LoRA weights are applied on top of the shared Gemini Nano v3 base model (~4 GB from OptGuideOnDeviceModel), specializing it for proofreading
For proofreading: user text goes into GIVEN_TEXT, model outputs corrected text
For classification: ORIGINAL_TEXT, PROOFREAD_TEXT, and CORRECTION are provided, model outputs a JSON label
Everything runs on-device, no data sent to servers

Key Details

LoRA fine-tuning: The 16.6 MB adaptation_weights.bin file contains Low-Rank Adaptation matrices that modify the base model's behavior without replacing it entirely
Structured output: The classification task outputs strict JSON ({"label": "Grammar"})
6 error categories: Spelling, Punctuation, Capitalization, Preposition, Missing words, Grammar