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

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use eugenehp/neutts 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 eugenehp/neutts:Q4_0
# Run inference directly in the terminal:
llama cli -hf eugenehp/neutts:Q4_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf eugenehp/neutts:Q4_0
# Run inference directly in the terminal:
llama cli -hf eugenehp/neutts:Q4_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 eugenehp/neutts:Q4_0
# Run inference directly in the terminal:
./llama-cli -hf eugenehp/neutts:Q4_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 eugenehp/neutts:Q4_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf eugenehp/neutts:Q4_0

Use Docker

docker model run hf.co/eugenehp/neutts:Q4_0

LM Studio
Jan
Ollama
How to use eugenehp/neutts with Ollama:
```
ollama run hf.co/eugenehp/neutts:Q4_0
```

Unsloth Studio

How to use eugenehp/neutts 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 eugenehp/neutts 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 eugenehp/neutts to start chatting

Using HuggingFace Spaces for Unsloth

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

How to use eugenehp/neutts with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf eugenehp/neutts:Q4_0

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": "eugenehp/neutts:Q4_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use eugenehp/neutts with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf eugenehp/neutts:Q4_0

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 eugenehp/neutts:Q4_0

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use eugenehp/neutts with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf eugenehp/neutts:Q4_0

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 "eugenehp/neutts:Q4_0" \
  --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 eugenehp/neutts with Docker Model Runner:
```
docker model run hf.co/eugenehp/neutts:Q4_0
```

Lemonade

How to use eugenehp/neutts with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull eugenehp/neutts:Q4_0

Run and chat with the model

lemonade run user.neutts-Q4_0

List all available models

lemonade list

neutts

File size: 1,400 Bytes

---
license: apache-2.0
pipeline_tag: audio-to-audio
library_name: rlx
tags:
- neucodec
- neutts
- rlx
---

# NeuCodec encoder (RLX staging)

NeuCodec encoder safetensors used by RLX NeuTTS voice clone.

| Field | Value |
|---|---|
| **Hub id** | [`eugenehp/neutts`](https://huggingface.co/eugenehp/neutts) |
| **Kind** | Converted / re-laid-out for RLX from an upstream checkpoint. |
| **RLX crate** | [`rlx-neutts`](https://github.com/MIT-RLX/rlx-models/tree/main/crates/rlx-neutts) |
| **Upstream** | https://huggingface.co/neuphonic/neucodec |

## Quick start

```bash
hf download eugenehp/neutts --local-dir .
export NEUTTS_ENCODER_PATH=neucodec_encoder.safetensors
```

## File highlights

- `neutts-air-Q4_0.gguf` (502.6 MiB)
- `neucodec_encoder.safetensors` (210.8 MiB)
- `neucodec_encoder_config.json` (301 B)

## Run with RLX

Clone [rlx-models](https://github.com/MIT-RLX/rlx-models), place this repo under `weights/tts/neutts` (or pass the path explicitly), then:

```bash
export NEUTTS_ENCODER_PATH=neucodec_encoder.safetensors
```

## License

Apache License 2.0 — see `LICENSE`. Inherit upstream terms when redistributing.

Original weights and authorship: https://huggingface.co/neuphonic/neucodec

## Maintenance

Cards and LFS attrs are regenerated from the local `weights/` tree in [rlx-models](https://github.com/MIT-RLX/rlx-models) via `python3 scripts/prepare_weights_hf.py`.