sd3.5

Lightweight inference model for generating high-quality images

CommonProductImageImage GenerationMachine Learning

Stable Diffusion 3.5 is a lightweight model designed for simple inference, incorporating a text encoder, VAE decoder, and core MM-DiT technology. This model aims to assist partner organizations in implementing SD3.5 and can be used to produce high-quality images. Its significance lies in its efficient inference capabilities and low resource requirements, allowing a wide user base to enjoy the art of image generation. The model adheres to the Stability AI Community License Agreement and is available for free.

Supports various text encoders
including OpenAI CLIP-L/14
OpenCLIP bigG
and Google T5-XXL.
Utilizes a 16-channel VAE decoder
eliminating the need for post-quantization convolution steps.
Core MM-DiT technology delivers efficient image generation capabilities.
Can generate images of various sizes and resolutions.
Supports image generation from text prompts.
Allows users to customize generation settings through command line parameters.

The target audience includes researchers
developers
and artists who can utilize Stable Diffusion 3.5 to generate creative image content for artistic endeavors or image-related research. Its lightweight nature also makes it suitable for resource-constrained users
such as small businesses and individual hobbyists.

Artists create unique artworks based on text prompts using Stable Diffusion 3.5.
Researchers use the model to study the latest advancements in image generation technology.
Developers integrate this model into their applications
providing users with the ability to generate personalized images.

1. Download the required model files from HuggingFace to your local `models` directory.
2. Set up and activate a Python virtual environment.
3. Use pip to install the dependencies listed in requirements.txt.
4. Run the `sd3_infer.py` script via the command line
providing the relevant text prompts.

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