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

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Serveurperso/chatterbox-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 Serveurperso/chatterbox-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Serveurperso/chatterbox-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 Serveurperso/chatterbox-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Serveurperso/chatterbox-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 Serveurperso/chatterbox-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Serveurperso/chatterbox-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 Serveurperso/chatterbox-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Serveurperso/chatterbox-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Serveurperso/chatterbox-GGUF:Q4_K_M

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

Unsloth Studio

How to use Serveurperso/chatterbox-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 Serveurperso/chatterbox-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 Serveurperso/chatterbox-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

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

Atomic Chat new
Docker Model Runner
How to use Serveurperso/chatterbox-GGUF with Docker Model Runner:
```
docker model run hf.co/Serveurperso/chatterbox-GGUF:Q4_K_M
```

Lemonade

How to use Serveurperso/chatterbox-GGUF with Lemonade:

Pull the model

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

Run and chat with the model

lemonade run user.chatterbox-GGUF-Q4_K_M

List all available models

lemonade list

Chatterbox GGUF

GGUF conversions of Chatterbox turbo and multilingual v3 for the llama.cpp mtmd TTS pipeline. Proof of concept built with @ngxson, under review: https://github.com/ngxson/llama.cpp/pull/107

Requires a build of the PR branch. Voice cloning takes any reference clip via --tts-speaker-file, sampling defaults per variant are embedded in the GGUFs (general.sampling.*).

llama-tts -m chatterbox-turbo-GGUF-Q8_0.gguf \
          -mm mmproj-chatterbox-turbo-GGUF-Q8_0.gguf \
          --tts-speaker-file ref.wav -p "Hello there." -o out.wav

Multilingual prompts carry a language tag: -p "[fr]Bonjour."

Downloads last month: 398

GGUF

Model size

0.5B params

Architecture

llama

Hardware compatibility

4-bit

8-bit

16-bit

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