LCM-LoRA SDXL

--- library_name: diffusers base_model: stabilityai/stable-diffusion-xl-base-1.0 tags: - lora - text-to-image license: openrail++ inference: false --- # Latent Consistency Model (LCM) LoRA: SDXL Latent Consistency Model (LCM) LoRA was proposed in [LCM-LoRA: A universal Stable-Diffusion Acceleration Module](https://arxiv.org/abs/2311.05556) by *Simian Luo, Yiqin Tan, Suraj Patil, Daniel Gu et al.* It is a distilled consistency adapter for [`stable-diffusion-xl-base-1.0`](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) that allows to reduce the number of inference steps to only between **2 - 8 steps**. | Model | Params / M | |----------------------------------------------------------------------------|------------| | [lcm-lora-sdv1-5](https://huggingface.co/latent-consistency/lcm-lora-sdv1-5) | 67.5 | | [lcm-lora-ssd-1b](https://huggingface.co/latent-consistency/lcm-lora-ssd-1b) | 105 | | [**lcm-lora-sdxl**](https://huggingface.co/latent-consistency/lcm-lora-sdxl) | **197M** | ## Usage LCM-LoRA is supported in 🤗 Hugging Face Diffusers library from version v0.23.0 onwards. To run the model, first install the latest version of the Diffusers library as well as `peft`, `accelerate` and `transformers`. audio dataset from the Hugging Face Hub: ```bash pip install --upgrade pip pip install --upgrade diffusers transformers accelerate peft ``` ***Note: For detailed usage examples we recommend you to check out our official [LCM-LoRA docs](https://huggingface.co/docs/diffusers/main/en/using-diffusers/inference_with_lcm_lora)*** ### Text-to-Image The adapter can be loaded with it's base model `stabilityai/stable-diffusion-xl-base-1.0`. Next, the scheduler needs to be changed to [`LCMScheduler`](https://huggingface.co/docs/diffusers/v0.22.3/en/api/schedulers/lcm#diffusers.LCMScheduler) and we can reduce the number of inference steps to just 2 to 8 steps. Please make sure to either disable `guidance_scale` or use values between 1.0 and 2.0. ```python import torch from diffusers import LCMScheduler, AutoPipelineForText2Image model_id = "stabilityai/stable-diffusion-xl-base-1.0" adapter_id = "latent-consistency/lcm-lora-sdxl" pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16") pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config) pipe.to("cuda") # load and fuse lcm lora pipe.load_l...

Source context: 42879 downloads · 775 likes · Pipeline text-to-image · Library diffusers · Repo latent-consistency/lcm-lora-sdxl

Source context: 34087 downloads · 771 likes · Pipeline text-to-image · Library diffusers · Repo latent-consistency/lcm-lora-sdxl