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Diffusers

Diffusers is an open-source Hugging Face library providing pretrained diffusion models, reusable components, and pipelines for generating or manipulating images, audio, video, and other data.

How 2 Manning books explain it

Build a Text-to-Image Generator (from Scratch)

Diffusers is an open-source software library providing implementations and pipelines for diffusion models and their image-generation workflows.

How it is used
Provides standardized interfaces for importing diffusion models and generating images from text prompts.
How deep it goes
Covers installation, pipeline use, U-Net inputs and outputs, and component roles while treating U-Net internals as a black box.
Examples
Demonstrates pretrained image generation, prompt batches, output grids, custom resolution, and classifier-free guidance.
What you can do after
Apply it via StableDiffusionPipeline to generate prompt-based images and configure precision, resolution, and guidance.

Read how Build a Text-to-Image Generator (from Scratch) explains diffusers →

Deep Learning with JAX

A library of pretrained and trainable diffusion-model pipelines for generating images, audio, video, and other outputs.

How it is used
Provides pretrained and trainable diffusion pipelines for generating images, audio, video, molecule structures, and other outputs.
How deep it goes
Demonstrates pipeline loading and configuration, while deferring detailed diffusion internals and model-training procedures.
Examples
Uses Stable Diffusion v1-5, a TPU backend check, FlaxStableDiffusionPipeline, bfloat16 parameters, and generated image outputs.
What you can do after
Apply it via FlaxStableDiffusionPipeline to load a pretrained model and begin generating images with JAX.

Read how Deep Learning with JAX explains diffusers →

Related concepts

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