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library_name: audio-interv
tags:
- ace-step
- activation-steering
- audio
- caa
- diffusion
- electronic-music
- interpretability
- music
- steering
---
# CAA — `electronic_music` (ACE-Step)
Steering vectors for the **electronic_music** concept on ACE-Step, computed via contrastive activation addition (CAA).
## Paper
TADA! Tuning Audio Diffusion Models through Activation Steering — [https://huggingface.co/papers/2602.11910](https://huggingface.co/papers/2602.11910)
## Quickstart
```python
from src.steering import SteerableACEModel, CAASteeringController
model = SteerableACEModel(device="cuda")
model.pipeline.load()
ctrl = CAASteeringController.from_pretrained("lukasz-staniszewski/ace-step-caa-rock-genre", alpha=20.0)
with model.steer(ctrl):
audio = model.generate(
prompt="instrumental music", lyrics="[inst]",
audio_duration=10.0, infer_step=30, manual_seed=0,
)
```
## Generation config
```json
{
"method": "standard_caa",
"concept": "electronic_music",
"lyrics": "[inst]",
"num_cfg_passes": 2,
"save_all_cfg_passes": true,
"audio_duration": 30.0,
"num_inference_steps": 30,
"seed": 10,
"device": "cuda",
"save_dir": "steering_vectors/caa",
"guidance_scale_text": 0.0,
"guidance_scale_lyric": 0.0,
"guidance_scale": 5.0,
"guidance_interval": 1.0,
"guidance_interval_decay": 0.0
}
```
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