How to use Zyphra/ZONOS3-Mini-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Zyphra/ZONOS3-Mini-hf", trust_remote_code=True)
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Zyphra/ZONOS3-Mini-hf", trust_remote_code=True, device_map="auto")
How to use Zyphra/ZONOS3-Mini-hf 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-hf", 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)
https://huggingface.co/Zyphra/ZONOS3-Mini-hf/resolve/main/tokenizer.json
hf download hf://Zyphra/ZONOS3-Mini-hf/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/Zyphra/ZONOS3-Mini-hf/resolve/main/tokenizer.json
