🤗 Diffusers
AssessTools
A Hugging Face library for inference, training, and composition of diffusion models.
Why it's here
Placed in Assess: 2 article(s) of evidence from 1 source(s), led by framework updates, with 2 in the last 30 days. Confidence 31%.
Evidence (2)
- 7Hugging Face Blog·7/23/2026framework_updateDiffusers Adds Native Nunchaku 4-bit Diffusion Support
Hugging Face Diffusers now supports loading Nunchaku 4-bit diffusion checkpoints directly with from_pretrained(), without local CUDA compilation or a separate inference engine. The update combines Nunchaku NVFP4 transformer kernels with bitsandbytes NF4 text encoders, cutting memory use and improving inference speed for supported hardware.
- 7Hugging Face Blog·7/17/2026framework_updateNVIDIA and Hugging Face add large-scale fine-tuning for Diffusers models
NVIDIA NeMo Automodel now integrates with 🤗 Diffusers to support distributed fine-tuning of video and image diffusion models directly from Hugging Face Hub checkpoints, without checkpoint conversion or model rewrites. The collaboration adds production-oriented training features such as memory-efficient sharding, latent caching, multiresolution bucketing, and configurable parallelism across multiple scales.