
# 

## Model Introduction

This model is trained using the [Civision/model training](https://modelscope.ai/civision/modelTraining) environment and computing resources provided by ModelScope.

* Model Type: LoRA
* Base Model: [ACE-Step/acestep-v15-xl-sft](https://modelscope.ai/models/ACE-Step/acestep-v15-xl-sft)
* Training Code: [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
* Data amount：48
* Total training steps：5000
* License: Apache-2.0

## Inference Code

Install [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio):

```bash
pip install diffsynth
```

Inference:

```python
from diffsynth.pipelines.ace_step import AceStepPipeline, ModelConfig
from diffsynth.utils.data.audio import save_audio
import torch

pipe = AceStepPipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",
    model_configs=[
        ModelConfig(model_id="ACE-Step/acestep-v15-xl-sft", origin_file_pattern="model-*.safetensors"),
        ModelConfig(model_id="ACE-Step/Ace-Step1.5", origin_file_pattern="Qwen3-Embedding-0.6B/model.safetensors"),
        ModelConfig(model_id="ACE-Step/Ace-Step1.5", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
    ],
    text_tokenizer_config=ModelConfig(model_id="ACE-Step/Ace-Step1.5", origin_file_pattern="Qwen3-Embedding-0.6B/"),
    silence_latent_config=ModelConfig(model_id="ACE-Step/Ace-Step1.5", origin_file_pattern="acestep-v15-turbo/silence_latent.pt"),
)
pipe.load_lora(pipe.dit, ModelConfig(model_id="Alexandrr/Kino2", origin_file_pattern="Kino2_c1-st5000.safetensors"))

prompt = "An explosive, high-energy pop-rock track with a strong anime theme song feel."
lyrics = "I Love you. Forever. I Love you. Forever."
audio = pipe(
    prompt=prompt,
    lyrics=lyrics,
    duration=160,
    bpm=100,
    keyscale="B minor",
    timesignature="4",
    vocal_language="zh",
    seed=1,
    num_inference_steps=50,
    cfg_scale=4.0,
)
save_audio(audio, pipe.vae.sampling_rate, "music.wav")
```


Kino2

Kino2_c1-st5000.safetensors

Files with SHA256: 768a83ddfb23594808afc241beb20e0761e15bf270f68547e80423f5a6790fd6