Instructions to use Zyphra/ZONOS3-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Zonos
How to use Zyphra/ZONOS3-Mini with Zonos:
# pip install git+https://github.com/Zyphra/Zonos.git import torchaudio from zonos.model import Zonos from zonos.conditioning import make_cond_dict model = Zonos.from_pretrained("Zyphra/ZONOS3-Mini", device="cuda") wav, sr = torchaudio.load("speaker.wav") # 5-10s reference clip speaker = model.make_speaker_embedding(wav, sr) cond = make_cond_dict(text="Hello, world!", speaker=speaker, language="en-us") codes = model.generate(model.prepare_conditioning(cond)) audio = model.autoencoder.decode(codes)[0].cpu() torchaudio.save("sample.wav", audio, model.autoencoder.sampling_rate) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Zyphra/ZONOS3-Mini 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 Zyphra/ZONOS3-Mini # Run inference directly in the terminal: llama cli -hf Zyphra/ZONOS3-Mini
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Zyphra/ZONOS3-Mini # Run inference directly in the terminal: llama cli -hf Zyphra/ZONOS3-Mini
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf Zyphra/ZONOS3-Mini # Run inference directly in the terminal: ./build/bin/llama cli -hf Zyphra/ZONOS3-Mini
Use Docker
docker model run hf.co/Zyphra/ZONOS3-Mini
- Llama new
- LM Studio
- Jan
- Ollama
How to use Zyphra/ZONOS3-Mini with Ollama:
ollama run hf.co/Zyphra/ZONOS3-Mini
- Unsloth Desktop
- Docker Model Runner
How to use Zyphra/ZONOS3-Mini with Docker Model Runner:
docker model run hf.co/Zyphra/ZONOS3-Mini
- Lemonade
How to use Zyphra/ZONOS3-Mini with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Zyphra/ZONOS3-Mini
Run and chat with the model
lemonade run user.ZONOS3-Mini-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Download registries/speaker_encoder_registry.json from Zyphra/ZONOS3-Mini: direct link, hf CLI and curl.
- Browser
- Download file 655 Bytes
-
https://huggingface.co/Zyphra/ZONOS3-Mini/resolve/main/registries/speaker_encoder_registry.json
- Command line
-
hf download hf://Zyphra/ZONOS3-Mini/registries/speaker_encoder_registry.json
-
curl -L -o speaker_encoder_registry.json https://huggingface.co/Zyphra/ZONOS3-Mini/resolve/main/registries/speaker_encoder_registry.json
655 Bytes
| { | |
| "ownmect_s2": { | |
| "type": "mect_fbank", | |
| "checkpoint": "speaker_encoders/ownmect_s2/ckpt_0037.pth", | |
| "sha256": "3cef65631f3161cbd8eacc6ea40e59a237c79656d85c7232dcbe0c8d07cae88f", | |
| "backbone_type": "MECT_B2", | |
| "backbone_config": { | |
| "moe_type": "token", | |
| "num_experts_shard": 2, | |
| "num_experts_token": 4, | |
| "top_k_shard": null, | |
| "top_k_token": null, | |
| "shard_scale": 1.0 | |
| }, | |
| "pooling": "ASTP", | |
| "embed_dim": 192, | |
| "sample_rate": 16000, | |
| "max_seconds": 60, | |
| "fbank": { | |
| "num_mel_bins": 80, | |
| "frame_length": 25, | |
| "frame_shift": 10, | |
| "dither": 0.0, | |
| "energy_floor": 0.0, | |
| "window_type": "hamming", | |
| "scale": 32768 | |
| } | |
| } | |
| } | |