README.md

---
license: mit
language: en
pipeline_tag: text-to-audio
base_model: hkchengrex/MMAudio
---

# Fine-tuned MMAudio Model

This repository contains a fine-tuned version of the **MMAudio** model, specializing in generating audio from video, image, and text prompts. The model was fine-tuned on a private dataset, resulting in the `cloud19/NSFW_MMaudio` checkpoint. Specializing in NSFW videos of various kinds.

**Original Project:** [hkchengrex/MMAudio](https://github.com/hkchengrex/MMAudio)

## Model Details

*   **Base Architecture:** `large_44k` (from the original MMAudio)
*   **Fine-tuning:** The model was fine-tuned on a private dataset of NSFW content to explore the model's adaptability to specific audio domains. Due to the nature of the training data, the generated audio may reflect mature themes.
*   **Capabilities:** Video-to-Audio, Image-to-Audio, Text-to-Audio.

## How to Use

This repository includes a fully functional Gradio (`app.py`). To run it locally, follow these steps. GPU 12-16 GB preferred.

**Prerequisites:**
*   Python 3.10+
*   Git and Git LFS (`git-lfs` must be installed)

### Step-by-Step Instructions

1.  **Clone the repository:**
    Open your terminal and clone the repository. `git-lfs` will automatically handle downloading the large model file.

    ```bash
    git clone https://huggingface.co/cloud19/NSFW_MMaudio
    cd NSFW_MMaudio
    ```

2.  **Set up a virtual environment (recommended):**
    ```bash
    python -m venv venv
    source venv/bin/activate
    # On Windows, use: venv\Scripts\activate
    ```

3.  **Install the required dependencies:**
    The `requirements.txt` file contains all necessary packages.

    ```bash
    pip install -r requirements.txt
    ```

4.  **Run the Gradio application:**
    This will launch a local web server.

    ```bash
    python app.py
    ```

Now you can use the web interface to generate audio with your fine-tuned model.

**Limitations:**
*   The model's output is heavily influenced by its training data.
*   **Content Warning:** Due to the NSFW nature of the fine-tuning dataset, the model may generate explicit or mature audio content. User discretion is advised.
*   Like all generative models, it may produce artifacts or unexpected results.

## Original Model Citation

All credit for the original architecture, code, and pre-trained models goes to the authors of MMAudio. Please refer to their repository for more details.

*   **Original GitHub:** [https://github.com/hkchengrex/MMAudio](https://github.com/hkchengrex/MMAudio)