Noggles9000

🚀 noggles9000 on Stable Diffusion

This is a Stable Diffusion model fine - tuned on the noggles9000 concept. It enables text - to - image generation related to this concept.

🚀 Quick Start

This is a Stable Diffusion model that has been fine - tuned on the noggles9000 concept using Dreambooth. You can use it by modifying the instance_prompt(s): nounfootball.jpg

✨ Features

• Concept Training: The model is trained on the noggles9000 concept, allowing for specific text - to - image generation.
• Custom Training: You can train your own concepts and upload them to the library.
• Multiple Running Methods: It can be run via A1111 Colab or diffusers.

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

Basic Usage

You can use the model by modifying the instance_prompt(s) as shown below:

# Use the model by setting the appropriate instance_prompt
# Here, we assume a simple Python - like pseudocode for illustration
# In a real - world scenario, you need to use relevant Stable Diffusion libraries
instance_prompt = "nounfootball.jpg"
# Code to generate image using the model with the prompt

Advanced Usage

If you want to train your own concepts, you can use [the fast - DreamBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast - stable - diffusion/blob/main/fast - DreamBooth.ipynb).

# Steps to train your own concept using the notebook
# This is a high - level pseudocode
# 1. Open the notebook in Colab
# 2. Follow the instructions in the notebook to prepare data and train the model

If you want to run your new concept via A1111 Colab, use [Fast - Colab - A1111](https://colab.research.google.com/github/TheLastBen/fast - stable - diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb).

# Steps to run the new concept via A1111 Colab
# This is a high - level pseudocode
# 1. Open the notebook in Colab
# 2. Load your trained model and relevant data
# 3. Run the code in the notebook to generate images

If you want to run your new concept via diffusers, use Colab Notebook for Inference and [Spaces with the Public Concepts loaded](https://huggingface.co/spaces/sd - dreambooth - library/stable - diffusion - dreambooth - concepts).

# Steps to run the new concept via diffusers
# This is a high - level pseudocode
# 1. Open the inference notebook in Colab
# 2. Install necessary libraries
# 3. Load your trained model and relevant data
# 4. Run the code in the notebook to generate images

📚 Documentation

The model is trained via Dreambooth on the [fast - DreamBooth.ipynb by TheLastBen](https://colab.research.google.com/github/TheLastBen/fast - stable - diffusion/blob/main/fast - DreamBooth.ipynb) notebook.

Sample pictures of this concept:

📄 License

The model is under the creativeml - openrail - m license.