Text-to-Speech
Transformers
ONNX
Safetensors
lingv3_tts
feature-extraction
audio
voice-cloning
multilingual
mixture-of-experts
speech-generation
custom_code
Instructions to use ml-resources/Ming-3.0-tts-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml-resources/Ming-3.0-tts-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="ml-resources/Ming-3.0-tts-tiny", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ml-resources/Ming-3.0-tts-tiny", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K