Patch Release: Support for SDXL Kohya-style LoRAs, Fix batched inference SDXL Img2Img, Improve watermarker
We still had some bugs ๐ in 0.19.1 some bugs, notably:
The official SD-XL 1.0 LoRA (Kohya-styled) is now supported thanks to https://github.com/huggingface/diffusers/pull/4287. You can try it as follows:
from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16)
pipe.load_lora_weights("stabilityai/stable-diffusion-xl-base-1.0", weight_name="sd_xl_offset_example-lora_1.0.safetensors")
pipe.to("cuda")
prompt = "beautiful scenery nature glass bottle landscape, purple galaxy bottle"
negative_prompt = "text, watermark"
image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=25).images[0]
In addition, a couple more SDXL LoRAs are now supported:
(SDXL 0.9:)
To know more details and the known limitations, please check out the documentation.
Thanks to @isidentical for their sincere help in the PR.
@bghira found that for SDXL Img2Img batched inference led to weird artifacts. That is fixed in: https://github.com/huggingface/diffusers/pull/4327.
Under some circumstances SD-XL 1.0 can download ONNX weights which is corrected in https://github.com/huggingface/diffusers/pull/4338.
https://github.com/huggingface/diffusers/pull/4346 allows the user to disable the watermarker under certain circumstances to improve the usability of SDXL.
Fetched April 7, 2026