Text to Image Generation with DreamShaper XL

This project utilizes the DreamShaper XL model for text-to-image generation. Given a text prompt, the model generates an image corresponding to the input text. The project employs the diffusers library for efficient generation and utilizes GPU acceleration for faster processing.

Setup Instructions

1. Ensure you have Python installed on your system.
2. Install the required libraries:

   pip install matplotlib torch diffusers
   

Usage

1. Run the provided script in your Python environment.
2. Enter your desired text prompt when prompted.
3. The script will generate and display the corresponding image.

Note

• Ensure you have a CUDA-enabled GPU for faster image generation.
• Adjust num_inference_steps and guidance_scale parameters for different image generation settings.
• For any issues or inquiries, please refer to the documentation of diffusers or the respective model documentation.

Some Generated Examples