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vllm-omni/examples/offline_inference/text_to_audio/README.md
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Zhang JianandClaude Opus 4.6 17acd0589a [Test] Add Stable Audio offline e2e TeaCache Test (#2377)
Signed-off-by: Zhang <jianmusings@gmail.com>
Signed-off-by: Zhang Jian <jianmusings@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 15:05:12 +08:00

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# Text-To-Audio
The `stabilityai/stable-audio-open-1.0` pipeline generates audio from text prompts.
## Prerequisites
If you use a gated model (e.g., `stabilityai/stable-audio-open-1.0`), ensure you have access:
1. **Accept Model License**: Visit the model page on Hugging Face (e.g., [stabilityai/stable-audio-open-1.0]) and accept the user agreement.
2. **Authenticate**: Log in to Hugging Face locally to access the gated model.
```bash
huggingface-cli login
```
## Local CLI Usage
```bash
python text_to_audio.py \
--model stabilityai/stable-audio-open-1.0 \
--prompt "The sound of a hammer hitting a wooden surface" \
--negative-prompt "Low quality" \
--seed 42 \
--guidance-scale 7.0 \
--audio-length 10.0 \
--num-inference-steps 100 \
--cache-backend tea_cache \
--output stable_audio_output.wav
```
Key arguments:
- `--prompt`: text description (string).
- `--negative-prompt`: negative prompt for classifier-free guidance.
- `--seed`: integer seed for deterministic generation.
- `--guidance-scale`: classifier-free guidance scale.
- `--audio-length`: audio duration in seconds.
- `--num-inference-steps`: diffusion sampling steps.(more steps = higher quality, slower).
- `--cache-backend`: cache acceleration backend. Stable Audio currently supports `tea_cache`.
- `--output`: path to save the generated WAV file.