Text-to-Speech
Transformers
ONNX
Safetensors
English
Chinese
bailing_moe_v3_audio
feature-extraction
audio
speech
automatic-speech-recognition
audio-understanding
audio-reasoning
speech-to-text
conversational
mixture-of-experts
custom_code
Instructions to use eshmoideas/Ming-audio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eshmoideas/Ming-audio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="eshmoideas/Ming-audio", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eshmoideas/Ming-audio", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 77 Bytes
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