lukasz-staniszewski/ace-step-cs-electronic-music-r8-tf6tf7

Concept Slider LoRA — electronic_music (r8, layers=tf6tf7) — ACE-Step

LoRA adapter trained with the Concept Sliders loss for steering ACE-Step audio generation toward the electronic_music concept. alpha modulates the active LoRA weight; set_alpha swaps weights without reloading.

• Rank: r8
• Target layers: tf6tf7

Paper

TADA! Tuning Audio Diffusion Models through Activation Steering — https://huggingface.co/papers/2602.11910

Files

• pytorch_lora_weights.safetensors — the LoRA weights.
• train_config.json — training hyperparameters.

Quickstart

from src.steering import SteerableACEModel, ConceptSlidersSteeringController

model = SteerableACEModel(device="cuda")
model.pipeline.load()
ctrl = ConceptSlidersSteeringController.from_pretrained("lukasz-staniszewski/ace-step-cs-electronic-music-r8-tf6tf7", alpha=1.0)

with model.steer(ctrl):
    for alpha in [-2, -1, 0, 1, 2]:
        ctrl.set_alpha(alpha)
        audio = model.generate(
            prompt="instrumental music", lyrics="[inst]",
            audio_duration=10.0, infer_step=30, manual_seed=0,
        )

Training config

{
  "concept": "electronic_music",
  "lora_config": {
    "r": 8,
    "lora_alpha": 1,
    "target_modules": [
      "to_q",
      "to_k",
      "to_v",
      "to_out.0",
      "add_q_proj",
      "add_k_proj",
      "add_v_proj",
      "to_add_out"
    ],
    "lora_dropout": 0.0,
    "bias": "none"
  },
  "lora_config_path": "steering/cs/lora_config_r8.json",
  "layers": "tf6tf7",
  "layers_to_transform": [
    6,
    7
  ],
  "iterations": 500,
  "lr": 0.0001,
  "weight_decay": 0.01,
  "eta": 7,
  "audio_duration": 10.0,
  "seed": 42,
  "max_grad_norm": 1.0,
  "gradient_checkpointing": true,
  "with_denoising": true,
  "max_denoising_steps": 50,
  "denoise_cfg_scale": 5.0,
  "num_lora_params": 983040,
  "frame_length": 108,
  "num_prompts": 50,
  "final_loss": 0.0213623046875,
  "avg_loss_last_50": 0.0623095703125
}