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 inclusionAI/Ming-3.0-audio-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/Ming-3.0-audio-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="inclusionAI/Ming-3.0-audio-tiny", 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("inclusionAI/Ming-3.0-audio-tiny", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from inclusionAI/Ming-3.0-audio-tiny: direct link, hf CLI and curl.
- Browser
- Download file 77 Bytes
-
https://huggingface.co/inclusionAI/Ming-3.0-audio-tiny/resolve/main/generation_config.json
- Command line
-
hf download hf://inclusionAI/Ming-3.0-audio-tiny/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/inclusionAI/Ming-3.0-audio-tiny/resolve/main/generation_config.json
77 Bytes
| { | |
| "eos_token_id": [ | |
| 156892, | |
| 156895 | |
| ], | |
| "pad_token_id": 156892 | |
| } | |