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

Libraries

How to use eugenehp/chatterbox with Chatterbox:

# pip install chatterbox-tts
import torchaudio as ta
from chatterbox.tts import ChatterboxTTS

model = ChatterboxTTS.from_pretrained(device="cuda")

text = "Ezreal and Jinx teamed up with Ahri, Yasuo, and Teemo to take down the enemy's Nexus in an epic late-game pentakill."
wav = model.generate(text)
ta.save("test-1.wav", wav, model.sr)

# If you want to synthesize with a different voice, specify the audio prompt
AUDIO_PROMPT_PATH="YOUR_FILE.wav"
wav = model.generate(text, audio_prompt_path=AUDIO_PROMPT_PATH)
ta.save("test-2.wav", wav, model.sr)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use eugenehp/chatterbox 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/chatterbox:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf eugenehp/chatterbox:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf eugenehp/chatterbox:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf eugenehp/chatterbox: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 eugenehp/chatterbox:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf eugenehp/chatterbox: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 eugenehp/chatterbox:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf eugenehp/chatterbox:Q4_K_M

Use Docker

docker model run hf.co/eugenehp/chatterbox:Q4_K_M

LM Studio
Jan
Ollama
How to use eugenehp/chatterbox with Ollama:
```
ollama run hf.co/eugenehp/chatterbox:Q4_K_M
```

Unsloth Studio

How to use eugenehp/chatterbox 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/chatterbox 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/chatterbox to start chatting

Using HuggingFace Spaces for Unsloth

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

Docker Model Runner
How to use eugenehp/chatterbox with Docker Model Runner:
```
docker model run hf.co/eugenehp/chatterbox:Q4_K_M
```

Lemonade

How to use eugenehp/chatterbox with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull eugenehp/chatterbox:Q4_K_M

Run and chat with the model

lemonade run user.chatterbox-Q4_K_M

List all available models

lemonade list

Atomic Chat

ChatterBox ONNX + RLX native (staging)

ChatterBox ONNX tree plus RLX native/ T3 extract (parity bins removed).

Field	Value
Hub id	`eugenehp/chatterbox`
Kind	Converted / re-laid-out for RLX from an upstream checkpoint.
RLX crate	`rlx-chatterbox`
Upstream	https://huggingface.co/synath/chatterbox-ONNX

Quick start

hf download eugenehp/chatterbox --local-dir .
cargo run -p rlx-chatterbox --release -- --model-dir .

File highlights

native/t3_lm.safetensors (976.2 MiB)
t3-q4_k_m.gguf (299.6 MiB)
onnx/cfm_estimator.onnx (273.0 MiB)
onnx/flow_encoder.onnx (177.2 MiB)
onnx/hift_head.onnx (79.6 MiB)
onnx/hift_stages.onnx (79.6 MiB)
weights.safetensors (77.6 MiB)
native/embed_tables.safetensors (58.8 MiB)
native/rope_cache.safetensors (32.0 MiB)
onnx/hift_src.onnx (12.6 MiB)
onnx/hift_f0.onnx (12.5 MiB)
onnx/conditional_decoder.onnx (6.1 MiB)
onnx/speech_encoder.onnx (1.1 MiB)
default_voice.wav (697.6 KiB)
onnx/language_model_q4f16.onnx (224.0 KiB)
onnx/language_model_fp16.onnx (168.6 KiB)

Run with RLX

Clone rlx-models, place this repo under weights/tts/chatterbox (or pass the path explicitly), then:

cargo run -p rlx-chatterbox --release -- --model-dir .

License

MIT — see LICENSE. Inherit upstream terms when redistributing.

Original weights and authorship: https://huggingface.co/synath/chatterbox-ONNX

Maintenance

Cards and LFS attrs are regenerated from the local weights/ tree in rlx-models via python3 scripts/prepare_weights_hf.py.

Downloads last month: 80

GGUF

Model size

0.5B params

Architecture

llama

Hardware compatibility

4-bit