Instructions to use michael-chan-000/tts-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michael-chan-000/tts-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="michael-chan-000/tts-v0")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("michael-chan-000/tts-v0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
vocence_miner_v9
English prompt-driven TTS. Built on Qwen3-TTS-12Hz-1.7B-VoiceDesign, finetuned on a large dataset.
from qwen_tts import Qwen3TTSModel
m = Qwen3TTSModel.from_pretrained("magma90909/vocence_miner_v9")
wavs, sr = m.generate_voice_design(text="Hello fellas.", instruct="Cute voice.", language="english")
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Model tree for michael-chan-000/tts-v0
Base model
magma90909/vocence_miner_v9