ACE-Step: AI Music Generation Powerhouse in Colab

(Please replace github.com/Reysajju/ACE-Step/blob/main/ACE-Step-Music-Generation.ipynb with the actual link to your Colab notebook if you create one in your repository. Otherwise, users can copy the commands below into a new Colab notebook.)

This repository provides guidance and commands for running the ACE-Step model to generate high-quality music using Google Colab. ACE-Step is a novel open-source foundation model for music generation.

Features of ACE-Step

• High-Quality Music Generation: Creates coherent and rich musical pieces.
• Fast Inference: Synthesizes music rapidly (e.g., up to 4 minutes of music in ~20 seconds on an A100 GPU).
• Diverse Styles & Genres: Supports various music styles and genres.
• Multiple Languages: Can generate music with lyrics in several languages. [1]
• Controllability: Offers features like lyric editing, variations, repainting, and potentially voice cloning. [1]
• Applications: Lyric2Vocal, Text2Samples, and upcoming features like RapMachine and StemGen. [1]
• Audio to Audio: Supports audio inputs for tasks like remixing or style transfer (as indicated by "Audio2Audio Demo support" in their updates). [1]
• Colab Ready: Easily run with a free GPU in Google Colab using the commands below.
• Memory Optimized: Updates have focused on reducing VRAM usage, making it more accessible. [1]

Prerequisites for Running (General)

• For Colab: A Google Account and a browser.
• For Local Setup (Advanced Users - refer to official ACE-Step docs for full details):
  • Python: Version 3.10 or later is recommended by ACE-Step.
  • Git: For cloning the official ACE-Step repository.
  • NVIDIA GPU: A CUDA-enabled GPU is generally required for good performance. ACE-Step has been optimized for lower VRAM (e.g., 8GB target).
  • CUDA Toolkit & cuDNN: Appropriate NVIDIA drivers and libraries.
  • Disk Space: For Python, dependencies, and the ACE-Step model.

Setup & Usage in Google Colab (Recommended)

1. Open a Google Colab Notebook:

   • You can click the "Open In Colab" badge above if you've set up a notebook in this repository.
   • Alternatively, go to colab.research.google.com and create a new notebook.

2. Set GPU Runtime:

   • In Colab, go to "Runtime" -> "Change runtime type".
   • Select "GPU" from the "Hardware accelerator" dropdown and click "Save".

3. Run the following commands in a code cell:

   # 1. Clone the Official ACE-Step Repository
   !git clone https://github.com/ace-step/ACE-Step.git
   
   # 2. Navigate into the project directory
   %cd ACE-Step
   
   # 3. Install Dependencies
   # This installs ACE-Step and its core dependencies in editable mode.
   print("Installing dependencies...")
   !pip install -e .
   print("Dependencies installed.")
   
   # 4. Run the ACE-Step Gradio Interface
   print("Starting ACE-Step Gradio interface...")
   # --share true : Creates a public Gradio link to access the UI.
   # --bf16 true : Uses bfloat16 precision for faster inference.
   # --cpu_offload true : Offloads model weights to CPU to save GPU VRAM.
   # --overlapped_decode true : Speeds up inference with overlapped decoding.
   # --torch_compile true : Optimizes the model with torch.compile() (works on Linux/Colab).
   !acestep --port 7865 --share true --bf16 true --cpu_offload true --overlapped_decode true --torch_compile true

4. Access the ACE-Step Interface:

   • After the last command finishes, look for a public URL in the output (e.g., Running on public URL: https://xxxxxx.gradio.live).
   • Open this URL in your browser to access the ACE-Step Gradio interface. You can then input text, lyrics, upload audio (for audio-to-audio features), and generate music.

Customization (within the ACE-Step Gradio UI)

Once the Gradio interface is running, you can typically customize:

• Input Mode: Text-to-Music, Audio-to-Audio (look for upload options in tabs like "Edit" or "Repainting" or a dedicated Audio2Audio tab).
• Tags/Description: Describe the genre, mood, instruments, etc.
• Lyrics: Input lyrics with structure tags like [verse], [chorus]. [1]
• Audio Duration: Set the length of the music to be generated. [1]
• Settings:
  • Basic Settings: Inference steps, guidance scale, seeds. [1]
  • Advanced Settings: Scheduler type, CFG type, etc. [1]
• Specific Tasks: Use dedicated tabs or modes for "Retake," "Repainting," "Edit," or "Extend" functionalities if available. [1]

Troubleshooting Common Colab Issues

• "No GPU backend selected": Ensure you've set the runtime to GPU (see Step 2).
• "ModuleNotFoundError": Double-check that !pip install -e . completed successfully without errors.
• "CUDA Out of Memory":
  • The flags --cpu_offload true and --bf16 true are included to help mitigate this.
  • Try generating shorter audio clips.
  • Restart the Colab runtime ("Runtime" -> "Disconnect and delete runtime") and try again. Sometimes Colab assigns GPUs with less available memory.
• For ACE-Step specific issues: Refer to the official ACE-Step GitHub Issues.

Official ACE-Step Resources

• GitHub Repository: https://github.com/ace-step/ACE-Step
• Project Page: https://ace-step.github.io/
• Hugging Face: Check their project page for links to models or spaces.
• Discord: They have a Discord server for community discussion (link usually on their GitHub).

License

This informational README.md and any associated Colab notebook in this repository can be considered under the MIT License (if you add one). The ACE-Step project itself is licensed under the Apache License 2.0. Please consult their official repository for full details and adhere to their licensing terms when using their software.

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