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 / README.md

BreyAIrev

Carte de modele bilingue

e174775 verified 3 days ago

preview code

Raw

History Blame Contribute Delete

2.9 kB

	---
	license: apache-2.0
	base_model: Qwen/Qwen2.5-Coder-14B-Instruct
	language:
	- fr
	- en
	pipeline_tag: text-generation
	tags:
	- gguf
	- ollama
	- cnc
	- gcode
	- g-code
	- machining
	- manufacturing
	- fanuc
	- siemens
	- heidenhain
	- qwen2.5-coder
	datasets:
	- BreyAIrev/cnc-gcode-expert
	---

	# 🛠️ 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](https://huggingface.co/BreyAIrev/AInewgen-CNC-Controller-Basic), le dataset [cnc-gcode-expert](https://huggingface.co/datasets/BreyAIrev/cnc-gcode-expert) et le Space [Cnc Gcode Auditor](https://huggingface.co/spaces/BreyAIrev).

	## Utilisation rapide (Ollama)

	```bash
	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.

	```bash
	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](https://revpcbaicloud.web.app) 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).