Real Vis_ Medium_2.0b

Introduction

RealVis Medium 2.0B is a fine-tuned model designed to generate high-quality, realistic, and photorealistic images. It is based on the Stable Diffusion 3.5 Medium model. The development of this model is ongoing, with further improvements anticipated.

Architecture

RealVis Medium is built on the Stable Diffusion 3.5 infrastructure. It focuses on enhancing the quality and realism of generated images, leveraging advancements in text-to-image generation techniques.

Training

The training of RealVis Medium 2.0B is structured into four stages:

1. Data Preparation:

   • Dataset collection and processing.
   • Image captioning for the dataset.

2. Model Training:

   • Currently at part 7 out of 15, with 1400 out of 3000 images processed.

3. Testing and Comparison:

   • Model testing and comparison with the base model are pending.

4. Release:

   • The model is yet to be officially released.

Guide: Running Locally

1. Prerequisites:

   • Ensure you have Python and necessary libraries installed.
   • Obtain the model files from the Hugging Face repository.

2. Setup:

   • Clone the model repository.
   • Install dependencies via a package manager like pip.

3. Execution:

   • Run the model using a script or through a Jupyter Notebook.
   • Use sample prompts to generate images.

4. Hardware Recommendations:

   • It is recommended to use cloud GPUs for efficient processing, such as those from AWS, Google Cloud, or Azure.

License

The model is provided under the "stabilityai-ai-community" license. Details can be found in the license document.