对于StableDiffusionXLPipeline,我们编译降噪器 (UNet) 和 VAE fromdiffusersimportStableDiffusionXLPipelineimporttorchpipe=StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0",torch_dtype=torch.bfloat16).to("cuda")## Compile the UNet and VAE.pipe.unet=torch.compile(pipe.un...
RunPod(SDXL Trainer) Paperspace Colab(pro)-AUTOMATIC1111 Colab(pro)-Dreambooth Dreambooth paper : https://dreambooth.github.io/ SD implementation by @XavierXiao : https://github.com/XavierXiao/Dreambooth-Stable-DiffusionAbout fast-stable-diffusion + DreamBooth Resources Readme License MIT ...
同时,stable-fast还拥有所有框架中最快的模型编译速度,不像AITemplate和TensorRT,它们需要耗费数分钟来完成模型的编译,stable-fast可以在10s内完成这一切。这是一个显著的优势! 更重要的是:stable-fast完全兼容SD15、SD21、SDXL、LCM甚至是最新的Stable Video Diffusion! 同时,如果你是SD Next的用户,那么官方在Dev分...
FastSDXL This is an efficient implementation of Stable-Diffusion-XL. I make the following improvements: Reconstruct the architecture of UNet. This UNet implementation is faster than others (Diffusers, Fooocus, etc.). If you are interested in this implementation, please see FastSDXL/BlockUNet.py...
Fast-stable diffusion (FSD) is a powerful tool in image processing that enables the creation of high-quality images by simulating the diffusion process of light in biological tissues. It uses a mathematical model to simulate how light spreads through different tissue types, resulting in images ...
NHWC&融合GroupNorm:stable-fast通过OpenAI的Triton实施了高效的融合NHWC GroupNorm+GELU运算子操作符,消除了channels last memory format下不必要的memory permutation。 全部trace模型:stable-fast改进了torch.jit.trace接口以适应复杂模型的追踪,大多数StableDiffusionPipeline的每个部分都可以被追踪并转换成TorchScript。它比...
Fast 1 step inference supported on runwayml/stable-diffusion-v1-5 model,select rupeshs/hypersd-sd1-5-1-step-lora lcm_lora model from the settings. Stable diffuion XL Works with LCM and LCM-OpenVINO mode. Hyper-SD SDXL 1 step - rupeshs/hyper-sd-sdxl-1-step Hyper-SD SDXL 1 step...
To optimize itsworkflows using the Stable Diffusion XL modelin production,Let’s Enhance, a pioneering AI startup, chose the NVIDIA AI inference platform. Product images with backgrounds created using Let’s Enhance platform powered by SDXL. ...
This paper introduces PIXART- α \alpha , a Transformer-based T2I diffusion model whose image generation quality is competitive with state-of-the-art image generators (e.g., Imagen, SDXL, and even Midjourney), reaching near-commercial application standards. Additionally, it supports high-...
release from niosomal film and dispersion according to different kinetic models Formulation Correlation coefficient (R2)* Zero order First order Higuchi diffusion Peppas Niosomal dispersion (N4) Niosomal film (N4F6) 0.9798±0.012 0.9526±0.015 0.9488±0.019 0.91852±0.021 Note: *Mean ± SD (n=3)...