Instructions to use 42ailab/AIWriter-V1-4B-Check-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use 42ailab/AIWriter-V1-4B-Check-Preview with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M # Run inference directly in the terminal: llama cli -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M # Run inference directly in the terminal: llama cli -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Use Docker
docker model run hf.co/42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
- LM Studio
- Jan
- vLLM
How to use 42ailab/AIWriter-V1-4B-Check-Preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "42ailab/AIWriter-V1-4B-Check-Preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "42ailab/AIWriter-V1-4B-Check-Preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
- Ollama
How to use 42ailab/AIWriter-V1-4B-Check-Preview with Ollama:
ollama run hf.co/42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
- Unsloth Desktop
- Pi
How to use 42ailab/AIWriter-V1-4B-Check-Preview with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use 42ailab/AIWriter-V1-4B-Check-Preview with Docker Model Runner:
docker model run hf.co/42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
- Lemonade
How to use 42ailab/AIWriter-V1-4B-Check-Preview with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Run and chat with the model
lemonade run user.AIWriter-V1-4B-Check-Preview-Q5_K_M
List all available models
lemonade list
- Hermes Agent
How to use 42ailab/AIWriter-V1-4B-Check-Preview with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use 42ailab/AIWriter-V1-4B-Check-Preview with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Configure Hermes
# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_MRun Hermes
hermesAIWriter Chinese Proofreading Model ยท V1 Preview
โ ๏ธ Preview release. V1 is not finalized. The stable release will be published at
42ailab/AIWriter-V1-4B-Checkafter the AIWriter launch event. This repository will be kept, not deleted (for reproducibility) and marked as superseded at that time. "V1" denotes the model generation, not a finalized version.
1. Introduction
AIWriter Chinese Proofreading Model is trained in-house by 42ailab for serious long-form Chinese writing: typos, word misuse, grammar, and punctuation.
What sets it apart from general-purpose LLMs doing proofreading is what it optimizes for:
General models optimize for finding everything. This model optimizes for holding back.
We measured three leading flagship models on sentences that contain no error at all โ 43.4%โ50.4% of them got edited anyway. (A fourth, kimi-k3, scored highest on the main metric but its false-edit rate has not been measured yet; it is listed in the table below with that column blank rather than silently dropped.)
For an author this is worse than a missed typo. A missed typo still gets caught by the editor; a quietly "improved" sentence stays in the book โ it reads fine, it just isn't the sentence you wrote anymore.
Key Features
- Low false-edit rate: 19.92% on error-free sentences โ less than half that of the three flagships we measured (43.4%โ50.4%);
- Guaranteed by training, not by prompting: "return the sentence unchanged when there is no error" is a behaviour learned from the training distribution, not an instruction in a system prompt;
- Purpose-built benchmark: accompanied by AIWriter CheckBench, which treats the false-edit rate as a first-class metric alongside the main score;
- Fully local: 4B parameters, runs on an ordinary laptop, works offline โ your manuscript never leaves your machine;
- Open weights: free for academic research and personal use.
2. Model Summary
| Base model | Qwen3-4B (Apache-2.0, Qwen Team) |
| Parameters | 4B |
| Context length | 4,096 |
| Recommended output | 192 tokens |
| Language | Simplified Chinese |
| Released formats | GGUF Q8_0 (4.28 GB) ยท Q5_K_M (2.89 GB) |
| License | AIWriter Model License 1.0 (free for academic & personal use; commercial use requires a licence) |
3. Evaluation
Results on AIWriter CheckBench ยท V1 Preview, a Chinese proofreading benchmark
built in-house by 42ailab. Target measures whether edits are correct;
False-edit measures whether error-free sentences were left alone:
| Model | Target | False-edit โ |
|---|---|---|
| kimi-k3 | 63.17 | โ |
| DeepSeek-V4.1-Flash | 59.34 | 45.3% |
| GLM-5.2 | 56.99 | 50.4% |
| qwen3.8-flash | 55.83 | 43.4% |
| This model (4B) | 50.53 | 19.92% |
Read the two columns separately. The flagships lead by 5โ13 points on Target, while their false-edit rate is 2.2โ2.5ร higher than this model's.
Scope: figures are from the public development set; baselines were measured in 2026-09 on the same set, with the same scorer and the same decoding settings. A held-out test set is reserved for the closed evaluation of the stable release, following standard benchmark practice.
The full evaluation design, training recipe and ablations will appear in the technical report and the accompanying papers.
4. Download & Deployment
This model is packaged for 42model, our local inference engine โ the recommended way to get it:
42model desktop
- Open Model Library โ Writing and download AIWriter Chinese Proofreading Model ยท V1 Preview;
- Pick a build:
Q8_0(4.28 GB) โ recommended, closest to the original weights;Q5_K_M(2.89 GB) โ 1.4 GB lighter, 0.7 points lower.
Downloading is all you need to do here โ AIWriter picks the model up on its own (next section).
Inside AIWriter
Once installed, open AIWriter โ the desktop app discovers the local engine automatically; no endpoint or key to configure. Click Proofread in the editor. Everything runs on your machine; your manuscript never leaves it.
Files
| File | Build | Size |
|---|---|---|
AIWriter-V1-4B-Check-Q8_0.gguf |
quality | 4.28 GB |
AIWriter-V1-4B-Check-Q5_K_M.gguf |
lightweight | 2.89 GB |
SHA-256 checksums are listed on the Files page.
5. Limitations
- It is a sentence-level proofreader; long documents must be segmented and reassembled by the application;
- It fixes objective errors only โ no stylistic rewriting or polishing;
- Training data is predominantly Simplified Chinese formal prose; internet slang, dialects and classical Chinese have not been systematically evaluated.
6. License & Attribution
- This model is released under the AIWriter Model License 1.0: free for academic research, teaching, evaluation and personal use (including fine-tuning and derivatives, with attribution); commercial use requires prior written permission (contact@42ailab.com).
- Intellectual property: the training methodology, data construction and evaluation design remain the property of 42ailab. This licence grants no patent rights.
- Base model: Qwen3-4B, ยฉ Qwen Team, Apache-2.0. Rights in the base model are unaffected by this licence โ anyone may obtain and use Qwen3-4B itself under Apache-2.0; this licence applies only to the part we trained on top of it.
- Training data comes from 42ailab's own corpus, synthetic data and public datasets.
7. Citation
The technical report and accompanying papers are in preparation; DOI and arXiv links will be added here on publication. In the meantime:
@misc{aiwriter2026check,
title = {AIWriter Chinese Proofreading Model V1 (AIWriter-V1-4B-Check)},
author = {Yang, Zhiping and {42ailab}},
year = {2026},
howpublished = {\url{https://huggingface.co/42ailab/AIWriter-V1-4B-Check-Preview}},
organization = {42ailab},
note = {Preview weights; technical report forthcoming, DOI and arXiv to be added here.
Base model Qwen3-4B (Apache-2.0). Contact: contact@42ailab.com}
}
Contact: contact@42ailab.com
About Us
42ailab โ an AI research lab exploring the boundaries of intelligence. Grounded in cognitive science, we work towards a deep integration of AI and human intelligence โ truly understanding and augmenting intelligence, carbon-based and silicon-based alike.
42model โ a high-performance local AI inference engine from 42ailab. Translation, transcription, recognition, chat and coding run free and private on your own machine; you can also fine-tune your own model with cloud compute and bring the weights back home.
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Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp# Start a local OpenAI-compatible server: llama serve -hf 42ailab/AIWriter-V1-4B-Check-Preview:Q5_K_M