Instructions to use chenyumo/moziAI-27B-MTP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use chenyumo/moziAI-27B-MTP 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 chenyumo/moziAI-27B-MTP:BF16
# Run inference directly in the terminal:
llama cli -hf chenyumo/moziAI-27B-MTP:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf chenyumo/moziAI-27B-MTP:BF16
# Run inference directly in the terminal:
llama cli -hf chenyumo/moziAI-27B-MTP:BF16

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 chenyumo/moziAI-27B-MTP:BF16
# Run inference directly in the terminal:
./llama-cli -hf chenyumo/moziAI-27B-MTP:BF16

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 chenyumo/moziAI-27B-MTP:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf chenyumo/moziAI-27B-MTP:BF16

Use Docker

docker model run hf.co/chenyumo/moziAI-27B-MTP:BF16

LM Studio
Jan

vLLM

How to use chenyumo/moziAI-27B-MTP with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "chenyumo/moziAI-27B-MTP"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chenyumo/moziAI-27B-MTP",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/chenyumo/moziAI-27B-MTP:BF16

Ollama
How to use chenyumo/moziAI-27B-MTP with Ollama:
```
ollama run hf.co/chenyumo/moziAI-27B-MTP:BF16
```
Unsloth Desktop

How to use chenyumo/moziAI-27B-MTP with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf chenyumo/moziAI-27B-MTP:BF16

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": "chenyumo/moziAI-27B-MTP:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use chenyumo/moziAI-27B-MTP with Docker Model Runner:
```
docker model run hf.co/chenyumo/moziAI-27B-MTP:BF16
```

Lemonade

How to use chenyumo/moziAI-27B-MTP with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull chenyumo/moziAI-27B-MTP:BF16

Run and chat with the model

lemonade run user.moziAI-27B-MTP-BF16

List all available models

lemonade list

Hermes Agent

How to use chenyumo/moziAI-27B-MTP with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf chenyumo/moziAI-27B-MTP:BF16

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 chenyumo/moziAI-27B-MTP:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use chenyumo/moziAI-27B-MTP with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf chenyumo/moziAI-27B-MTP:BF16

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 "chenyumo/moziAI-27B-MTP:BF16" \
  --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"

moziAI-27B-MTP / MODIFICATIONS.md

chenyumo

license: 合规整改 — LICENSE-APACHE/NOTICE/MODIFICATIONS + 上游许可表述复核(Qwen3.8-27B=Apache-2.0)

31c29a3 verified 11 days ago

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Modifications Notice / 修改声明

本文件依据 Apache License, Version 2.0 第 4(b) 条 的要求发布：分发衍生作品时，必须使任何被修改的文件带有显著声明，说明该文件已被修改。

This file is published to satisfy Apache License, Version 2.0, Section 4(b), which requires that any modified files carry prominent notices stating that they were changed.

1. 原始作品 / Original work

项目	内容
上游基底模型	Qwen3.8-27B（Dense）
上游许可	Apache License, Version 2.0
本作品	MoziAI-27B-MTP（moziAI-27B-V3.8）
修改人	Chen Yumo / 陈雨墨 / chenyumo166
修改时间	2026-08-10 ~ 2026-09-01

2. 修改内容 / What was changed

MoziAI 团队对原始作品进行了以下修改：

The MoziAI team made the following changes to the original work:

继续训练 / 微调 — 在金融领域数据上进行继续预训练与监督微调 Continued training / fine-tuning — continued pre-training and supervised fine-tuning on financial-domain data.
重新量化 — 使用自研 MoziSmartBit 智能量化算法对权重重新量化（Q4_K_M 级别，GGUF 格式） Requantization of the weights with the MoziAI-developed MoziSmartBit smart quantization algorithm (Q4_K_M class, GGUF).
保留 MTP 权重 — 完整保留 Qwen3.8 架构原生 MTP （Multi-Token Prediction）推测解码层 MTP weights preserved — the native MTP (Multi-Token Prediction) speculative decoding layer of the Qwen3.8 architecture is fully preserved.
对话模板 — 新增自定义 chat template，注入 MoziAI 身份标识、动态七维思考指令与 LOOP 迭代指令 Chat template — added a custom chat template injecting the MoziAI identity marker, seven-dimensional thinking instructions and LOOP iteration instructions.
视觉投影器 — 新增 mmproj 视觉投影器文件 Vision projector — added mmproj projector artifacts.
文档与脚手架 — 新增/改写 README、docs、发布脚本 Documentation and scaffolding — added/rewrote README, docs and release scripts.

3. 被修改 / 新增的文件清单 / Modified & added files

文件	状态
`moziAI-27B-MTP-V3.8-Q4_K_M-Qwen3.8-27B.gguf`	由上游权重修改（继续训练 + 重新量化）
`mmproj/27B/moziAI-27B-mmproj-BF16-V1.0.gguf`	新增
`V3.8/chat-template-moziai-27B-V3.8.jinja`	新增
`README.md`、`README.modelscope.md`、`V3.8/README.*.md`	新增/改写
`LICENSE.md`、`LICENSE-APACHE`、`NOTICE`	新增/改写

4. 未修改的上游权利 / Upstream rights not modified

本声明仅记录 MoziAI 团队的修改行为，不改变任何上游组件的许可状态。继承自 Qwen 的组件持续受 Apache License, Version 2.0 约束，见 LICENSE-APACHE；上游版权与归属声明见 NOTICE。

This statement only records the MoziAI team's modifications. It does not alter the license status of any upstream component. The inherited Qwen components remain governed by Apache License, Version 2.0 — see LICENSE-APACHE. Upstream copyright and attribution notices are in NOTICE.

5. 上游文件名的保留 / Retention of upstream notices

原始上游作品中的版权、专利、商标与归属声明（Apache License 2.0 第 4(c) 条要求保留的部分）均未被移除或隐藏。

No copyright, patent, trademark or attribution notice from the original upstream work (as required to be retained by Apache License 2.0, Section 4(c)) has been removed or obscured.

本文件最后更新：2026-09-12 / Last updated: 2026-09-12

License

License: see the MoziAI Model License (English v2.0). This model contains upstream components governed by the Apache License 2.0 (Qwen3.8-27B). Upstream copyright and attribution notices: NOTICE; modifications made by this team: MODIFICATIONS.md.