Instructions to use CMSManhattan/JiRackDeltaNet_180b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use CMSManhattan/JiRackDeltaNet_180b 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 CMSManhattan/JiRackDeltaNet_180b:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf CMSManhattan/JiRackDeltaNet_180b:Q3_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf CMSManhattan/JiRackDeltaNet_180b:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf CMSManhattan/JiRackDeltaNet_180b:Q3_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf CMSManhattan/JiRackDeltaNet_180b:Q3_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf CMSManhattan/JiRackDeltaNet_180b:Q3_K_M

Use Docker

docker model run hf.co/CMSManhattan/JiRackDeltaNet_180b:Q3_K_M

Llama new
LM Studio
Jan

vLLM

How to use CMSManhattan/JiRackDeltaNet_180b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CMSManhattan/JiRackDeltaNet_180b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CMSManhattan/JiRackDeltaNet_180b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/CMSManhattan/JiRackDeltaNet_180b:Q3_K_M

Ollama
How to use CMSManhattan/JiRackDeltaNet_180b with Ollama:
```
ollama run hf.co/CMSManhattan/JiRackDeltaNet_180b:Q3_K_M
```
Unsloth Desktop

How to use CMSManhattan/JiRackDeltaNet_180b with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf CMSManhattan/JiRackDeltaNet_180b:Q3_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": "CMSManhattan/JiRackDeltaNet_180b:Q3_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use CMSManhattan/JiRackDeltaNet_180b with Docker Model Runner:
```
docker model run hf.co/CMSManhattan/JiRackDeltaNet_180b:Q3_K_M
```

Lemonade

How to use CMSManhattan/JiRackDeltaNet_180b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull CMSManhattan/JiRackDeltaNet_180b:Q3_K_M

Run and chat with the model

lemonade run user.JiRackDeltaNet_180b-Q3_K_M

List all available models

lemonade list

Hermes Agent

How to use CMSManhattan/JiRackDeltaNet_180b with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf CMSManhattan/JiRackDeltaNet_180b:Q3_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 CMSManhattan/JiRackDeltaNet_180b:Q3_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use CMSManhattan/JiRackDeltaNet_180b with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf CMSManhattan/JiRackDeltaNet_180b:Q3_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 "CMSManhattan/JiRackDeltaNet_180b:Q3_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"

kgrabko commited on Sep 30

Commit

f0a4535

verified ·

1 Parent(s): cc1fcd5

Update README.md

Browse files

Files changed (1) hide show

README.md +12 -2

README.md CHANGED Viewed

@@ -152,7 +152,16 @@ Once a JiRack container is running, open your browser at `http://localhost:7869`
 ## Licensing
-- **Model weights:** JiRack DeltaNet 180B is a derivative of [Qwen/Qwen3.8-Flash-Next](https://huggingface.co/Qwen/Qwen3.8-Flash-Next) and is distributed under the **Qwen Community License 1.0** ([LICENSE](https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/main/LICENSE)). Keep the copyright and license notice with all copies. Review the license terms for commercial Model-as-a-Service and AI work-assistant (coding / office) products, which require a separate license from Qwen.
 - The Docker image with UI and pre-built Ollama quantizations are separate commercial products.
 - All JiRack UI clients are provided under a commercial license. The UI clients can be used for free together with the official JiRack Docker containers, as long as they are not redistributed separately.
@@ -259,4 +268,5 @@ For joint venture opportunities, hardware integration, or licensing inquiries:
 - **Location:** New York, USA
 ## License
-Qwen Community License 1.0 — see [LICENSE](https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/main/LICENSE). Copyright 2026 Qwen. JiRack conversion and QAT © 2025-2026 Konstantin Vladimirovich Grabko, CMS Manhattan JiRack Technology.

 ## Licensing
+This repository is dual-licensed: the model weights and the JiRack code are licensed separately.
+| Component | License |
+|---|---|
+| **Model weights** (safetensors, GGUF) — a derivative of [Qwen/Qwen3.8-Flash-Next](https://huggingface.co/Qwen/Qwen3.8-Flash-Next) | **Qwen Community License 1.0** — [LICENSE](https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/main/LICENSE), Copyright 2026 Qwen |
+| **JiRack code and tools** (`JiRackDeltaNet_180b.py`, conversion, QAT training, export and test scripts) | **MIT License** — © 2025-2026 Konstantin Vladimirovich Grabko, CMS Manhattan JiRack Technology |
+| **JiRack Docker images with UI, pre-built Ollama quantizations, JiRack UI clients** | Commercial license (see below) |
+- **Weights:** the Qwen Community License continues to apply to the weights, including the JiRack-converted and quantized versions. Keep the Qwen copyright and license notice with all copies. Commercial Model-as-a-Service and AI work-assistant (coding / office) products built on these weights require a separate license from Qwen — review the license terms before such use.
+- **Code:** the MIT License covers the JiRack source code only. It does not change the license of the weights.
 - The Docker image with UI and pre-built Ollama quantizations are separate commercial products.
 - All JiRack UI clients are provided under a commercial license. The UI clients can be used for free together with the official JiRack Docker containers, as long as they are not redistributed separately.
 - **Location:** New York, USA
 ## License
+- **Model weights:** Qwen Community License 1.0 — see [LICENSE](https://huggingface.co/Qwen/Qwen3.8-Flash-Next/blob/main/LICENSE). Copyright 2026 Qwen.
+- **JiRack code and tools:** MIT License — see `LICENSE-CODE`. © 2025-2026 Konstantin Vladimirovich Grabko, CMS Manhattan JiRack Technology.