Realistic_ Vision_ V6.0_ B1_no V A E

Introduction

Realistic Vision V6.0 "New Vision" is an update aimed at enhancing realism and photorealism in generated images. This model is in a beta phase with gradual updates planned until full release. It is suggested to use this model with a Variational Autoencoder (VAE) to improve image quality and reduce artifacts.

Architecture

The model supports various resolutions for different types of portraits and full-body images. These include:

• Face Portrait: 896x896
• Portrait: 896x896, 768x1024
• Half Body: 768x1024, 640x1152
• Full Body: 896x896, 768x1024, 640x1152, 1024x768, 1152x640

Improvements are ongoing to increase resolution and address issues like mutations and duplications in image generation.

Training

The model is trained to support both SFW and NSFW content, with ongoing improvements for various anatomical features. It employs advanced sampling techniques to refine image quality, such as DPM++ SDE Karras and DPM++ 2M SDE, with recommended steps and parameters for optimal results.

Guide: Running Locally

To run the Realistic Vision V6.0 model locally, follow these steps:

1. Setup Environment: Ensure you have a Python environment ready. Install necessary libraries, including the Hugging Face transformers and diffusers libraries.

2. Download Model: Obtain the model files from the Hugging Face repository.

3. Configure Parameters: Use the recommended samplers and settings for generation. For high-resolution images, consider using Hires.Fix with specified denoising steps and strengths.

4. Generate Images: Execute the model using appropriate prompts and parameters to generate desired images.

For optimal performance, utilizing cloud GPUs such as those offered by AWS, Google Cloud, or Azure is recommended.

License

The Realistic Vision V6.0 model is distributed under the CreativeML Open RAIL-M license. This license allows for various uses while ensuring proper attribution and adherence to specified guidelines.