Memory-efficient Diffusion Transformers with Quanto and Diffusers

Stable Diffusion with 🧨 Diffusers

Exploring Quantization Backends in Diffusers

Introducing Modular Diffusers - Composable Building Blocks for Diffusion Pipelines

Diffusers welcomes Stable Diffusion 3

Overview of natively supported quantization schemes in 🤗 Transformers

Diffusers welcomes Stable Diffusion 3.5 Large

Bringing Nunchaku 4-bit Diffusion Inference to Diffusers

Quality-Aware Modulation for Diffusion Transformers

arXiv:2606. 30934v1 Announce Type: new Abstract: Modern text-to-image diffusion models, such as diffusion transformers (DiT), rely on timestep or prompt embeddings to modulate the strength of the denoising process in each timestep.

Stable Diffusion XL on Mac with Advanced Core ML Quantization

A Gentle Introduction to 8-bit Matrix Multiplication for transformers at scale using transformers, accelerate and bitsandbytes

KroQuant: Kronecker-Structured Block Transforms for Efficient Post-Training Quantization of Diffusion Transformers

arXiv:2607. 21446v1 Announce Type: new Abstract: Post-training quantization (PTQ) of diffusion transformers (DiTs) to W4A4 severely degrades output quality, because activations entering each linear layer contain outliers that 4-bit formats cannot represent.

Diffusers welcomes FLUX-2