Hugging Face Diffusers
In order to implement Stable Diffusion model using GitHub repository is not beginner friendly. To make it more appealing to the user HuggingFace released Diffusers, an open-source repository for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Further just like HuggingFace transformers, even diffusers support various pipelines which makes running state-of-art models run withing one-two lines of code.
Pipeline is the easiest way to use a pretrained diffusion system for running the inference. It is an end-to-end system containing the model and the scheduler. The pipeline works on cleaning up an image by introducing random noise matching the desired output size and running it through the model multiple times. In each step, the model anticipates the residual noise, and the scheduler utilizes this information to generate a less noisy image.
So, let’s go build now.
Build Text To Image with HuggingFace Diffusers
This article will implement the Text 2 Image application using the Hugging Face Diffusers library. We will demonstrate two different pipelines with 2 different pre-trained Stable Diffusion models. Before we dive into code implementation, let us understand Stable Diffusion.
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