Instructions to use abliter8-ai/Roo-Voice-NeuTTS-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use abliter8-ai/Roo-Voice-NeuTTS-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="abliter8-ai/Roo-Voice-NeuTTS-GGUF",
	filename="roo-neutts-q4_k_m.gguf",
)

llm.create_chat_completion(
	messages = "\"The answer to the universe is 42\""
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use abliter8-ai/Roo-Voice-NeuTTS-GGUF 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 abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf abliter8-ai/Roo-Voice-NeuTTS-GGUF: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 abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf abliter8-ai/Roo-Voice-NeuTTS-GGUF: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 abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M

Use Docker

docker model run hf.co/abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use abliter8-ai/Roo-Voice-NeuTTS-GGUF with Ollama:
```
ollama run hf.co/abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M
```

Unsloth Studio

How to use abliter8-ai/Roo-Voice-NeuTTS-GGUF 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 abliter8-ai/Roo-Voice-NeuTTS-GGUF 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 abliter8-ai/Roo-Voice-NeuTTS-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for abliter8-ai/Roo-Voice-NeuTTS-GGUF to start chatting

How to use abliter8-ai/Roo-Voice-NeuTTS-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abliter8-ai/Roo-Voice-NeuTTS-GGUF: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": "abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use abliter8-ai/Roo-Voice-NeuTTS-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abliter8-ai/Roo-Voice-NeuTTS-GGUF: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 abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use abliter8-ai/Roo-Voice-NeuTTS-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abliter8-ai/Roo-Voice-NeuTTS-GGUF: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 "abliter8-ai/Roo-Voice-NeuTTS-GGUF: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 abliter8-ai/Roo-Voice-NeuTTS-GGUF with Docker Model Runner:
```
docker model run hf.co/abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M
```

Lemonade

How to use abliter8-ai/Roo-Voice-NeuTTS-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull abliter8-ai/Roo-Voice-NeuTTS-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Roo-Voice-NeuTTS-GGUF-Q4_K_M

List all available models

lemonade list

Roo-Voice-NeuTTS-GGUF

Single-voice identity-locked fine-tune of NeuTTS-Air (Qwen2.5-0.5B backbone) — the custom voice model behind the Roo Voice desktop app.

Current file: v2 (checkpoint-2000) — TEST release. A v3 train with expanded lexical coverage is in progress and will replace this as the shipping model.

Reference-free: text in, one fixed voice out. Greedy decoding (temp 0).
Phonemization: espeak-ng en-gb, phonemizer settings must match training.
Decode speech codes with NeuCodec (or the int8 ONNX decoder for on-device use).
Speech-token mapping when serving via llama.cpp /completion + return_tokens: code = token_id − 151671; stop at 151670 (<|SPEECH_GENERATION_END|>).

File	Quant	Size	Note
roo-neutts-q4_k_m.gguf	Q4_K_M	441 MB	app default; ear-checked
roo-neutts-q8_0.gguf	Q8_0	568 MB	headroom option; ear-checked

Q4_0 is deliberately absent — it degraded under greedy decoding in testing.

Downloads last month: -

GGUF

Model size

0.6B params

Architecture

qwen2

Hardware compatibility

4-bit

8-bit

Model tree for abliter8-ai/Roo-Voice-NeuTTS-GGUF

Base model

neuphonic/neutts-air

Quantized

(8)

this model