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

Libraries

How to use McaTech/Nonet with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="McaTech/Nonet",
	filename="ChatNONET-135m-tuned-q8_0.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use McaTech/Nonet 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 McaTech/Nonet:Q8_0
# Run inference directly in the terminal:
llama cli -hf McaTech/Nonet:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf McaTech/Nonet:Q8_0
# Run inference directly in the terminal:
llama cli -hf McaTech/Nonet:Q8_0

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 McaTech/Nonet:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf McaTech/Nonet:Q8_0

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 McaTech/Nonet:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf McaTech/Nonet:Q8_0

Use Docker

docker model run hf.co/McaTech/Nonet:Q8_0

LM Studio
Jan

vLLM

How to use McaTech/Nonet with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/McaTech/Nonet:Q8_0

Ollama
How to use McaTech/Nonet with Ollama:
```
ollama run hf.co/McaTech/Nonet:Q8_0
```

Unsloth Studio

How to use McaTech/Nonet with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for McaTech/Nonet to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for McaTech/Nonet to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for McaTech/Nonet to start chatting

Atomic Chat new
Docker Model Runner
How to use McaTech/Nonet with Docker Model Runner:
```
docker model run hf.co/McaTech/Nonet:Q8_0
```

Lemonade

How to use McaTech/Nonet with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull McaTech/Nonet:Q8_0

Run and chat with the model

lemonade run user.Nonet-Q8_0

List all available models

lemonade list

McaTech commited on Jun 28, 2025

Commit

22712e5

verified ·

1 Parent(s): 2dedfb1

Update README.md

Browse files

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README.md +3 -5

README.md CHANGED Viewed

@@ -49,10 +49,6 @@ NONET is intended for lightweight offline use, particularly on local devices lik
 - Local assistants (no internet required)
 - Embedded Android or Python apps
-### Downstream Use
-- Try the **Android app**: [Download ChatNONET APK](https://drive.google.com/file/d/1-5Ozx_VsOUBS5_b4yS40MCaNZge_5_1f/view?usp=sharing)
 ### Out-of-Scope Use
 - Long-form text generation
@@ -70,7 +66,9 @@ NONET may reproduce biases present in its base models or fine-tuning data. Outpu
 - Avoid over-reliance for personal or legal advice
 ## How to Get Started with the Model
 ```bash
 # Clone llama.cpp and build it
 git clone https://github.com/ggerganov/llama.cpp

 - Local assistants (no internet required)
 - Embedded Android or Python apps
 ### Out-of-Scope Use
 - Long-form text generation
 - Avoid over-reliance for personal or legal advice
 ## How to Get Started with the Model
+### For Android Devices
+- Try the **Android app**: [Download ChatNONET APK](https://drive.google.com/file/d/1-5Ozx_VsOUBS5_b4yS40MCaNZge_5_1f/view?usp=sharing)
+### You can also build llama.cpp your own and run it
 ```bash
 # Clone llama.cpp and build it
 git clone https://github.com/ggerganov/llama.cpp