Instructions to use BreyAIrev/AInewgen-CNC-Controller-Complete with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use BreyAIrev/AInewgen-CNC-Controller-Complete 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 BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_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 BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_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 BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M

Use Docker

docker model run hf.co/BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M

LM Studio
Jan

vLLM

How to use BreyAIrev/AInewgen-CNC-Controller-Complete with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M

Ollama
How to use BreyAIrev/AInewgen-CNC-Controller-Complete with Ollama:
```
ollama run hf.co/BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M
```

Unsloth Studio

How to use BreyAIrev/AInewgen-CNC-Controller-Complete 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 BreyAIrev/AInewgen-CNC-Controller-Complete 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 BreyAIrev/AInewgen-CNC-Controller-Complete to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for BreyAIrev/AInewgen-CNC-Controller-Complete to start chatting

How to use BreyAIrev/AInewgen-CNC-Controller-Complete with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use BreyAIrev/AInewgen-CNC-Controller-Complete with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_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 BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use BreyAIrev/AInewgen-CNC-Controller-Complete with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_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 "BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_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"

Docker Model Runner
How to use BreyAIrev/AInewgen-CNC-Controller-Complete with Docker Model Runner:
```
docker model run hf.co/BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M
```

Lemonade

How to use BreyAIrev/AInewgen-CNC-Controller-Complete with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull BreyAIrev/AInewgen-CNC-Controller-Complete:Q4_K_M

Run and chat with the model

lemonade run user.AInewgen-CNC-Controller-Complete-Q4_K_M

List all available models

lemonade list

🛠️ AInewgen CNC Controller — Complete (14B)

[English below]

Modèle expert CNC & G-code d'AInewgen : génération de G-code de qualité production pour Fanuc, Siemens, Heidenhain, GRBL et LinuxCNC. Fine-tuné à partir de Qwen2.5-Coder-14B et distribué en GGUF Q4_K_M (9 Go), prêt pour Ollama, llama.cpp et LM Studio — il tourne sur un GPU 16 Go ou en CPU.

C'est la version complète de notre gamme CNC : voir aussi AInewgen-CNC-Controller-Basic, le dataset cnc-gcode-expert et le Space Cnc Gcode Auditor.

Utilisation rapide (Ollama)

ollama run hf.co/BreyAIrev/AInewgen-CNC-Controller-Complete

Prompt système recommandé :

Tu es un expert CNC. Tu génères du G-code Fanuc, Siemens et Heidenhain de qualité
production. Tu réponds toujours avec du code complet, commenté, avec paramètres de
coupe justifiés et vérifications de sécurité avant usinage.

Capacités

Cycles de perçage/taraudage (G81-G84), poches, contournage, filetage (G76)
Compensations d'outil (G41/G42/G43), décalages (G54-G59)
Paramètres de coupe par matériau (aluminium, acier, inox, plastiques)
Diagnostics d'erreurs et vérifications de sécurité avant usinage
Bilingue : instructions en français ou en anglais

Détails techniques


Base	Qwen2.5-Coder-14B-Instruct (Apache-2.0)
Format	GGUF Q4_K_M — 9,0 Go
Contexte	32k tokens
Entraînement	Fine-tuning LoRA sur corpus CNC spécialisé AInewgen

🛠️ AInewgen CNC Controller — Complete (14B) (English)

AInewgen's expert CNC & G-code model: production-grade G-code generation for Fanuc, Siemens, Heidenhain, GRBL and LinuxCNC. Fine-tuned from Qwen2.5-Coder-14B, shipped as GGUF Q4_K_M (9 GB) — runs on a 16 GB GPU or CPU via Ollama, llama.cpp or LM Studio.

ollama run hf.co/BreyAIrev/AInewgen-CNC-Controller-Complete

Covers drilling/tapping cycles, pocketing, threading, tool compensation, per-material cutting parameters, error diagnostics and pre-machining safety checks. Instructions in French or English.

About AInewgen

AInewgen is a Canadian 🍁 company building specialized AI for electronics (PCB), scientific computing and manufacturing.

License

Apache-2.0 (same as the Qwen2.5-Coder base). Attribution appreciated: AInewgen CNC Controller Complete (BreyAIrev, 2026).

Downloads last month: 7

GGUF

Model size

15B params

Architecture

qwen2

Hardware compatibility

4-bit

Model tree for BreyAIrev/AInewgen-CNC-Controller-Complete

Base model

Qwen/Qwen2.5-14B

Finetuned

Qwen/Qwen2.5-Coder-14B

Finetuned

Qwen/Qwen2.5-Coder-14B-Instruct

Quantized

(115)

this model

BreyAIrev
/

AInewgen-CNC-Controller-Complete

🛠️ AInewgen CNC Controller — Complete (14B)

Utilisation rapide (Ollama)

Capacités

Détails techniques

🛠️ AInewgen CNC Controller — Complete (14B) (English)

About AInewgen

License

Model tree for BreyAIrev/AInewgen-CNC-Controller-Complete

Dataset used to train BreyAIrev/AInewgen-CNC-Controller-Complete