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
Add SGLang-Omni serving instructions to README
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by JustinTong - opened
README.md
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The validated Tiny SGLang profile uses one GPU and provides text output. See the [SGLang example](https://github.com/inclusionAI/Ming-3.0-audio-flash/blob/main/examples/sglang_audio_chat.py) for client usage.
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## Evaluation
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The shared benchmark figures below include results for both Ming-3.0-audio-tiny and Ming-3.0-audio-flash.
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The validated Tiny SGLang profile uses one GPU and provides text output. See the [SGLang example](https://github.com/inclusionAI/Ming-3.0-audio-flash/blob/main/examples/sglang_audio_chat.py) for client usage.
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### SGLang-Omni
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[SGLang-Omni](https://sgl-project.github.io/sglang-omni/) serves transcription, audio chat, and speech synthesis from one server. The Tiny checkpoint fits on a single GPU; `--talker.gpu 0` colocates speech synthesis with the other stages:
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```bash
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sgl-omni serve --model-path inclusionAI/Ming-3.0-audio-tiny --talker.gpu 0
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```
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The server exposes OpenAI-compatible `/v1/audio/transcriptions`, `/v1/audio/speech`, and `/v1/chat/completions` endpoints. The [SGLang-Omni cookbook](https://sgl-project.github.io/sglang-omni/cookbook/ming3_audio.html) shows client examples; the same requests work with the Tiny model name.
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## Evaluation
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The shared benchmark figures below include results for both Ming-3.0-audio-tiny and Ming-3.0-audio-flash.
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