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@@ -204,6 +121,16 @@ Rather than building yet another end-to-end text-to-music pipeline, our vision i - ๐ธ Creates full instrumental backing that complements the input vocals, making it easy to add professional-sounding accompaniment to any vocal recording +## ๐ Roadmap + +- [x] Release training code ๐ฅ +- [x] Release LoRA training code ๐ฅ +- [ ] Release RapMachine LoRA ๐ค +- [ ] Release ControlNet training code ๐ฅ +- [ ] Release Singing2Accompaniment ControlNet ๐ฎ +- [ ] Release evaluation performance and technical report ๐ + + ## ๐ฅ๏ธ Hardware Performance We have evaluated ACE-Step across different hardware setups, yielding the following throughput results: @@ -218,6 +145,79 @@ We have evaluated ACE-Step across different hardware setups, yielding the follow We use RTF (Real-Time Factor) to measure the performance of ACE-Step. Higher values indicate faster generation speed. 27.27x means to generate 1 minute of music, it takes 2.2 seconds (60/27.27). The performance is measured on a single GPU with batch size 1 and 27 steps. + +## ๐ฆ Installation + +### 1. Clone the Repository +First, clone the ACE-Step repository to your local machine and navigate into the project directory: +```bash +git clone https://github.com/ace-step/ACE-Step.git +cd ACE-Step +``` + +### 2. Prerequisites +Ensure you have the following installed: + +* `Python`: Version 3.10 or later is recommended. You can download it from [python.org](https://www.python.org/). +* `Conda` or `venv`: For creating a virtual environment (Conda is recommended). + +### 3. Set Up a Virtual Environment + +It is highly recommended to use a virtual environment to manage project dependencies and avoid conflicts. Choose one of the following methods: + +#### Option A: Using Conda + +1. **Create the environment** named `ace_step` with Python 3.10: + ```bash + conda create -n ace_step python=3.10 -y + ``` + +2. **Activate the environment:** + ```bash + conda activate ace_step + ``` + +#### Option B: Using venv + +1. **Navigate to the cloned ACE-Step directory.** + +2. **Create the virtual environment** (commonly named `venv`): + ```bash + python -m venv venv + ``` + +3. **Activate the environment:** + * **On Windows (cmd.exe):** + ```bash + venv\Scripts\activate.bat + ``` + * **On Windows (PowerShell):** + ```powershell + .\venv\Scripts\Activate.ps1 + ``` + *(If you encounter execution policy errors, you might need to run `Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope Process` first)* + * **On Linux / macOS (bash/zsh):** + ```bash + source venv/bin/activate + ``` + +### 4. Install Dependencies +Once your virtual environment is activated: +**a.** (Windows Only) If you are on Windows and plan to use an NVIDIA GPU, install PyTorch with CUDA support first: + +```bash +pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126 +``` +(Adjust cu126 if you have a different CUDA version. For other PyTorch installation options, refer to the [official PyTorch website](https://pytorch.org/get-started/locally/)). + +**b.** Install ACE-Step and its core dependencies: +```bash +pip install -e . +``` + +The ACE-Step application is now installed. The GUI works on Windows, macOS, and Linux. For instructions on how to run it, please see the [Usage](#-usage) section. + + ## ๐ Usage  @@ -237,6 +237,18 @@ acestep --checkpoint_path /path/to/checkpoint --port 7865 --device_id 0 --share If you are using macOS, please use `--bf16 false` to avoid errors. #### ๐ API Usage +If you intend to integrate ACE-Step as a library into your own Python projects, you can install the latest version directly from GitHub using the following pip command. + +**Direct Installation via pip:** + +1. **Ensure Git is installed:** This method requires Git to be installed on your system and accessible in your system's PATH. +2. **Execute the installation command:** + ```bash + pip install git+[https://github.com/ace-step/ACE-Step.git](https://github.com/ace-step/ACE-Step.git) + ``` + It's recommended to use this command within a virtual environment to avoid conflicts with other packages. + +Once the installation is complete, you can import and use the ACE-Step API as shown below: ```python from acestep.api import ACEStep @@ -247,7 +259,7 @@ audio_out = model.infer( prompt="upbeat pop, catchy melody, female singer", lyrics="[verse]\nSun is shining bright today\nFeeling happy, come what may", audio_duration=5.0, # 5 seconds - infer_step=20 # Fewer steps for speed + infer_step=20 # Fewer steps for speed ) audio_out.save_wav("output.wav") @@ -307,6 +319,12 @@ The ACE-Step interface provides several tabs for different music generation and The `examples/input_params` directory contains sample input parameters that can be used as references for generating music. +## ๐๏ธ Architecture + +
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