diffusers/pr_14358/en/_app/immutable/nodes/8.gPPHhPCT.js

import"../chunks/DsnmJJEf.js";import{i as wl,h as Ml,C as Sl,H as d,D as a,E as Tl,s as Nl,a as c}from"../chunks/BtE7mKSK.js";import{p as kl,o as Rl,s as e,f as _,a as f,b as Ul,c as r,d as u,r as o,n as s}from"../chunks/jDjavuwI.js";import{E as p}from"../chunks/SrSJA0zO.js";const Jl='{"title":"LoRA","local":"lora","sections":[{"title":"LoraBaseMixin","local":"diffusers.loaders.lora_base.LoraBaseMixin","sections":[],"depth":2},{"title":"StableDiffusionLoraLoaderMixin","local":"diffusers.loaders.StableDiffusionLoraLoaderMixin","sections":[],"depth":2},{"title":"StableDiffusionXLLoraLoaderMixin","local":"diffusers.loaders.StableDiffusionXLLoraLoaderMixin","sections":[],"depth":2},{"title":"SD3LoraLoaderMixin","local":"diffusers.loaders.SD3LoraLoaderMixin","sections":[],"depth":2},{"title":"FluxLoraLoaderMixin","local":"diffusers.loaders.FluxLoraLoaderMixin","sections":[],"depth":2},{"title":"Flux2LoraLoaderMixin","local":"diffusers.loaders.Flux2LoraLoaderMixin","sections":[],"depth":2},{"title":"ErnieImageLoraLoaderMixin","local":"diffusers.loaders.ErnieImageLoraLoaderMixin","sections":[],"depth":2},{"title":"LTX2LoraLoaderMixin","local":"diffusers.loaders.LTX2LoraLoaderMixin","sections":[],"depth":2},{"title":"CogVideoXLoraLoaderMixin","local":"diffusers.loaders.CogVideoXLoraLoaderMixin","sections":[],"depth":2},{"title":"Mochi1LoraLoaderMixin","local":"diffusers.loaders.Mochi1LoraLoaderMixin","sections":[],"depth":2},{"title":"AuraFlowLoraLoaderMixin","local":"diffusers.loaders.AuraFlowLoraLoaderMixin","sections":[],"depth":2},{"title":"LTXVideoLoraLoaderMixin","local":"diffusers.loaders.LTXVideoLoraLoaderMixin","sections":[],"depth":2},{"title":"SanaLoraLoaderMixin","local":"diffusers.loaders.SanaLoraLoaderMixin","sections":[],"depth":2},{"title":"HeliosLoraLoaderMixin","local":"diffusers.loaders.HeliosLoraLoaderMixin","sections":[],"depth":2},{"title":"HunyuanVideoLoraLoaderMixin","local":"diffusers.loaders.HunyuanVideoLoraLoaderMixin","sections":[],"depth":2},{"title":"Lumina2LoraLoaderMixin","local":"diffusers.loaders.Lumina2LoraLoaderMixin","sections":[],"depth":2},{"title":"CogView4LoraLoaderMixin","local":"diffusers.loaders.CogView4LoraLoaderMixin","sections":[],"depth":2},{"title":"WanLoraLoaderMixin","local":"diffusers.loaders.WanLoraLoaderMixin","sections":[],"depth":2},{"title":"SkyReelsV2LoraLoaderMixin","local":"diffusers.loaders.SkyReelsV2LoraLoaderMixin","sections":[],"depth":2},{"title":"AmusedLoraLoaderMixin","local":"diffusers.loaders.AmusedLoraLoaderMixin","sections":[],"depth":2},{"title":"AnimaLoraLoaderMixin","local":"diffusers.loaders.AnimaLoraLoaderMixin","sections":[],"depth":2},{"title":"AceStepLoraLoaderMixin","local":"diffusers.loaders.AceStepLoraLoaderMixin","sections":[],"depth":2},{"title":"HiDreamImageLoraLoaderMixin","local":"diffusers.loaders.HiDreamImageLoraLoaderMixin","sections":[],"depth":2},{"title":"QwenImageLoraLoaderMixin","local":"diffusers.loaders.QwenImageLoraLoaderMixin","sections":[],"depth":2},{"title":"ZImageLoraLoaderMixin","local":"diffusers.loaders.ZImageLoraLoaderMixin","sections":[],"depth":2},{"title":"CosmosLoraLoaderMixin","local":"diffusers.loaders.CosmosLoraLoaderMixin","sections":[],"depth":2},{"title":"KandinskyLoraLoaderMixin","local":"diffusers.loaders.KandinskyLoraLoaderMixin","sections":[],"depth":2},{"title":"Ideogram4LoraLoaderMixin","local":"diffusers.loaders.Ideogram4LoraLoaderMixin","sections":[],"depth":2},{"title":"Krea2LoraLoaderMixin","local":"diffusers.loaders.Krea2LoraLoaderMixin","sections":[],"depth":2},{"title":"LoraBaseMixin","local":"diffusers.loaders.lora_base.LoraBaseMixin","sections":[],"depth":2}],"depth":1}';var Dl=u('<meta name="hf:doc:metadata"/>'),m=u("<p>Example:</p> <!>",1),Cr=u("<p>Examples:</p> <!>",1),Zl=u(`<p></p> <!> <!> <p>LoRA is a fast and lightweight training method that inserts and trains a significantly smaller number of parameters instead of all the model parameters. This produces a smaller file (~100 MBs) and makes it easier to quickly train a model to learn a new concept. LoRA weights are typically loaded into the denoiser, text encoder or both. The denoiser usually corresponds to a UNet (<a href="/docs/diffusers/pr_14358/en/api/models/unet2d-cond#diffusers.UNet2DConditionModel">UNet2DConditionModel</a>, for example) or a Transformer (<a href="/docs/diffusers/pr_14358/en/api/models/sd3_transformer2d#diffusers.SD3Transformer2DModel">SD3Transformer2DModel</a>, for example). There are several classes for loading LoRA weights:</p> <ul><li><code>StableDiffusionLoraLoaderMixin</code> provides functions for loading and unloading, fusing and unfusing, enabling and disabling, and more functions for managing LoRA weights. This class can be used with any model.</li> <li><code>StableDiffusionXLLoraLoaderMixin</code> is a <a href="../../api/pipelines/stable_diffusion/stable_diffusion_xl">Stable Diffusion (SDXL)</a> version of the <code>StableDiffusionLoraLoaderMixin</code> class for loading and saving LoRA weights. It can only be used with the SDXL model.</li> <li><code>SD3LoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/blog/sd3" rel="nofollow">Stable Diffusion 3</a>.</li> <li><code>FluxLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux" rel="nofollow">Flux</a>.</li> <li><code>CogVideoXLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/cogvideox" rel="nofollow">CogVideoX</a>.</li> <li><code>Mochi1LoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/mochi" rel="nofollow">Mochi</a>.</li> <li><code>AuraFlowLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/fal/AuraFlow" rel="nofollow">AuraFlow</a>.</li> <li><code>LTXVideoLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/ltx_video" rel="nofollow">LTX-Video</a>.</li> <li><code>SanaLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/sana" rel="nofollow">Sana</a>.</li> <li><code>HeliosLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/helios" rel="nofollow">HunyuanVideo</a>.</li> <li><code>HunyuanVideoLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/hunyuan_video" rel="nofollow">HunyuanVideo</a>.</li> <li><code>Lumina2LoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/lumina2" rel="nofollow">Lumina2</a>.</li> <li><code>WanLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/wan" rel="nofollow">Wan</a>.</li> <li><code>SkyReelsV2LoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/skyreels_v2" rel="nofollow">SkyReels-V2</a>.</li> <li><code>CogView4LoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/cogview4" rel="nofollow">CogView4</a>.</li> <li><code>AmusedLoraLoaderMixin</code> is for the <code>AmusedPipeline</code>.</li> <li><code>AnimaLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/anima" rel="nofollow">Anima</a>.</li> <li><code>AceStepLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/ace_step" rel="nofollow">ACE-Step</a>.</li> <li><code>HiDreamImageLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/hidream" rel="nofollow">HiDream Image</a></li> <li><code>QwenImageLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/qwen" rel="nofollow">Qwen Image</a>.</li> <li><code>ZImageLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/zimage" rel="nofollow">Z-Image</a>.</li> <li><code>Flux2LoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux2" rel="nofollow">Flux2</a>.</li> <li><code>ErnieImageLoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/ernie_image" rel="nofollow">Ernie-Image</a>.</li> <li><code>LTX2LoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/ltx2" rel="nofollow">Flux2</a>.</li> <li><code>LoraBaseMixin</code> provides a base class with several utility methods to fuse, unfuse, unload, LoRAs and more.</li></ul> <blockquote class="tip"><p>To learn more about how to load LoRA weights, see the <a href="../../tutorials/using_peft_for_inference">LoRA</a> loading guide.</p></blockquote> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Utility class for handling LoRAs.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Delete an adapter’s LoRA layers from the pipeline.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Disables the active LoRA layers of the pipeline.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Enables the active LoRA layers of the pipeline.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Hotswap adapters without triggering recompilation of a model or if the ranks of the loaded adapters are
different.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Fuses the LoRA parameters into the original parameters of the corresponding blocks.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Gets the list of the current active adapters.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Gets the current list of all available adapters in the pipeline.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Set the currently active adapters for use in the pipeline.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Moves the LoRAs listed in <code>adapter_names</code> to a target device. Useful for offloading the LoRA to the CPU in case
you want to load multiple adapters and free some GPU memory.</p> <p>After offloading the LoRA adapters to CPU, as long as the rest of the model is still on GPU, the LoRA adapters
can no longer be used for inference, as that would cause a device mismatch. Remember to set the device back to
GPU before using those LoRA adapters for inference.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Reverses the effect of <a href="https://huggingface.co/docs/diffusers/main/en/api/loaders#diffusers.loaders.LoraBaseMixin.fuse_lora" rel="nofollow"><code>pipe.fuse_lora()</code></a>.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Unloads the LoRA parameters.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Writes the state dict of the LoRA layers (optionally with metadata) to disk.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into Stable Diffusion <a href="/docs/diffusers/pr_14358/en/api/models/unet2d-cond#diffusers.UNet2DConditionModel">UNet2DConditionModel</a> and <a href="https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel" rel="nofollow"><code>CLIPTextModel</code></a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>This will load the LoRA layers specified in <code>state_dict</code> into <code>text_encoder</code></p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>This will load the LoRA layers specified in <code>state_dict</code> into <code>unet</code>.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA weights specified in <code>pretrained_model_name_or_path_or_dict</code> into <code>self.unet</code> and <code>self.text_encoder</code>.</p> <p>All kwargs are forwarded to <code>self.lora_state_dict</code>.</p> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details on how the state dict is
loaded.</p> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details on how the state dict is
loaded into <code>self.unet</code>.</p> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder">load_lora_into_text_encoder()</a> for more details on how the state
dict is loaded into <code>self.text_encoder</code>.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Return state dict for lora weights and the network alphas.</p> <blockquote class="warning"><p>> We support loading A1111 formatted LoRA checkpoints in a limited capacity. > > This function is
experimental and might change in the future.</p></blockquote></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Save the LoRA parameters corresponding to the UNet and text encoder.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into Stable Diffusion XL <a href="/docs/diffusers/pr_14358/en/api/models/unet2d-cond#diffusers.UNet2DConditionModel">UNet2DConditionModel</a>, <a href="https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel" rel="nofollow"><code>CLIPTextModel</code></a>, and <a href="https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModelWithProjection" rel="nofollow"><code>CLIPTextModelWithProjection</code></a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>This will load the LoRA layers specified in <code>state_dict</code> into <code>text_encoder</code></p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>This will load the LoRA layers specified in <code>state_dict</code> into <code>unet</code>.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Return state dict for lora weights and the network alphas.</p> <blockquote class="warning"><p>> We support loading A1111 formatted LoRA checkpoints in a limited capacity. > > This function is
experimental and might change in the future.</p></blockquote></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/sd3_transformer2d#diffusers.SD3Transformer2DModel">SD3Transformer2DModel</a>, <a href="https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel" rel="nofollow"><code>CLIPTextModel</code></a>, and <a href="https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModelWithProjection" rel="nofollow"><code>CLIPTextModelWithProjection</code></a>.</p> <p>Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/stable_diffusion/stable_diffusion_3#diffusers.StableDiffusion3Pipeline">StableDiffusion3Pipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>This will load the LoRA layers specified in <code>state_dict</code> into <code>text_encoder</code></p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/flux_transformer#diffusers.FluxTransformer2DModel">FluxTransformer2DModel</a>, <a href="https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel" rel="nofollow"><code>CLIPTextModel</code></a>.</p> <p>Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/flux#diffusers.FluxPipeline">FluxPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>This will load the LoRA layers specified in <code>state_dict</code> into <code>text_encoder</code></p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Save the LoRA parameters corresponding to the UNet and text encoder.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Reverses the effect of <a href="https://huggingface.co/docs/diffusers/main/en/api/loaders#diffusers.loaders.LoraBaseMixin.fuse_lora" rel="nofollow"><code>pipe.fuse_lora()</code></a>.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Unloads the LoRA parameters.</p> <!></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/flux2_transformer#diffusers.Flux2Transformer2DModel">Flux2Transformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/flux2#diffusers.Flux2Pipeline">Flux2Pipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/ernie_image_transformer2d#diffusers.ErnieImageTransformer2DModel">ErnieImageTransformer2DModel</a>. Specific to <code>ErnieImagePipeline</code>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/ltx2_video_transformer3d#diffusers.LTX2VideoTransformer3DModel">LTX2VideoTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/ltx2#diffusers.LTX2Pipeline">LTX2Pipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/cogvideox_transformer3d#diffusers.CogVideoXTransformer3DModel">CogVideoXTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/cogvideox#diffusers.CogVideoXPipeline">CogVideoXPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/mochi_transformer3d#diffusers.MochiTransformer3DModel">MochiTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/mochi#diffusers.MochiPipeline">MochiPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/aura_flow_transformer2d#diffusers.AuraFlowTransformer2DModel">AuraFlowTransformer2DModel</a> Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/aura_flow#diffusers.AuraFlowPipeline">AuraFlowPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/ltx_video_transformer3d#diffusers.LTXVideoTransformer3DModel">LTXVideoTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/ltx_video#diffusers.LTXPipeline">LTXPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/sana_transformer2d#diffusers.SanaTransformer2DModel">SanaTransformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/sana#diffusers.SanaPipeline">SanaPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/helios_transformer3d#diffusers.HeliosTransformer3DModel">HeliosTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/helios#diffusers.HeliosPipeline">HeliosPipeline</a> and <a href="/docs/diffusers/pr_14358/en/api/pipelines/helios#diffusers.HeliosPyramidPipeline">HeliosPyramidPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/hunyuan_video_transformer_3d#diffusers.HunyuanVideoTransformer3DModel">HunyuanVideoTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/hunyuan_video#diffusers.HunyuanVideoPipeline">HunyuanVideoPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/lumina2_transformer2d#diffusers.Lumina2Transformer2DModel">Lumina2Transformer2DModel</a>. Specific to <code>Lumina2Text2ImgPipeline</code>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/wan_transformer_3d#diffusers.WanTransformer3DModel">WanTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/cogview4#diffusers.CogView4Pipeline">CogView4Pipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/wan_transformer_3d#diffusers.WanTransformer3DModel">WanTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/wan#diffusers.WanPipeline">WanPipeline</a> and <code>[WanImageToVideoPipeline</code>].</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/skyreels_v2_transformer_3d#diffusers.SkyReelsV2Transformer3DModel">SkyReelsV2Transformer3DModel</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Save the LoRA parameters corresponding to the UNet and text encoder.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/cosmos_transformer3d#diffusers.CosmosTransformer3DModel">CosmosTransformer3DModel</a> and <a href="/docs/diffusers/pr_14358/en/api/pipelines/anima#diffusers.AnimaTextConditioner">AnimaTextConditioner</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/ace_step_transformer#diffusers.AceStepTransformer1DModel">AceStepTransformer1DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/ace_step#diffusers.AceStepPipeline">AceStepPipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/hidream_image_transformer#diffusers.HiDreamImageTransformer2DModel">HiDreamImageTransformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/hidream#diffusers.HiDreamImagePipeline">HiDreamImagePipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/qwenimage_transformer2d#diffusers.QwenImageTransformer2DModel">QwenImageTransformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/qwenimage#diffusers.QwenImagePipeline">QwenImagePipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/z_image_transformer2d#diffusers.ZImageTransformer2DModel">ZImageTransformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/z_image#diffusers.ZImagePipeline">ZImagePipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/cosmos_transformer3d#diffusers.CosmosTransformer3DModel">CosmosTransformer3DModel</a>, Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/cosmos#diffusers.Cosmos2_5_PredictBasePipeline">Cosmos2_5_PredictBasePipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <code>Kandinsky5Transformer3DModel</code>,</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/ideogram4_transformer2d#diffusers.Ideogram4Transformer2DModel">Ideogram4Transformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/ideogram4#diffusers.Ideogram4Pipeline">Ideogram4Pipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Load LoRA layers into <a href="/docs/diffusers/pr_14358/en/api/models/krea2_transformer2d#diffusers.Krea2Transformer2DModel">Krea2Transformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14358/en/api/pipelines/krea2#diffusers.Krea2Pipeline">Krea2Pipeline</a>.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>fuse_lora()</code> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet">load_lora_into_unet()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a> for more details.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights">save_lora_weights()</a> for more information.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>See <code>unfuse_lora()</code> for more details.</p></div></div> <!> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Utility class for handling LoRAs.</p> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Delete an adapter’s LoRA layers from the pipeline.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Disables the active LoRA layers of the pipeline.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Enables the active LoRA layers of the pipeline.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Hotswap adapters without triggering recompilation of a model or if the ranks of the loaded adapters are
different.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Fuses the LoRA parameters into the original parameters of the corresponding blocks.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Gets the list of the current active adapters.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Gets the current list of all available adapters in the pipeline.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Set the currently active adapters for use in the pipeline.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Moves the LoRAs listed in <code>adapter_names</code> to a target device. Useful for offloading the LoRA to the CPU in case
you want to load multiple adapters and free some GPU memory.</p> <p>After offloading the LoRA adapters to CPU, as long as the rest of the model is still on GPU, the LoRA adapters
can no longer be used for inference, as that would cause a device mismatch. Remember to set the device back to
GPU before using those LoRA adapters for inference.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Reverses the effect of <a href="https://huggingface.co/docs/diffusers/main/en/api/loaders#diffusers.loaders.LoraBaseMixin.fuse_lora" rel="nofollow"><code>pipe.fuse_lora()</code></a>.</p></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Unloads the LoRA parameters.</p> <!></div> <div class="docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"><!> <p>Writes the state dict of the LoRA layers (optionally with metadata) to disk.</p></div></div> <!> <p></p>`,1);function Gl(Qs,Ps){kl(Ps,!1),Rl(()=>{new URLSearchParams(window.location.search).get("fw")}),wl();var qr=Zl();Ml("yjofn9",t=>{var n=Dl();Nl(n,"content",Jl),f(t,n)});var Yr=e(_(qr),2);Sl(Yr,{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"});var zr=e(Yr,2);d(zr,{title:"LoRA",local:"lora",headingTag:"h1"});var Qr=e(zr,8);d(Qr,{title:"LoraBaseMixin",local:"diffusers.loaders.lora_base.LoraBaseMixin",headingTag:"h2"});var h=e(Qr,2),Pr=r(h);a(Pr,{name:"class diffusers.loaders.lora_base.LoraBaseMixin",anchor:"diffusers.loaders.lora_base.LoraBaseMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L478",parameters:[]});var g=e(Pr,4),Er=r(g);a(Er,{name:"delete_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L840",parameters:[{name:"adapter_names",val:": list[str] | str"}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters.adapter_names",description:`<strong>adapter_names</strong> (<code>list[str, str]</code>) &#x2014;
The names of the adapters to delete.`,name:"adapter_names"}]});var Es=e(Er,4);p(Es,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image
<span class="hljs-keyword">import</span> torch

pipeline = AutoPipelineForText2Image.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(
    <span class="hljs-string">&quot;jbilcke-hf/sdxl-cinematic-1&quot;</span>, weight_name=<span class="hljs-string">&quot;pytorch_lora_weights.safetensors&quot;</span>, adapter_names=<span class="hljs-string">&quot;cinematic&quot;</span>
)
pipeline.delete_adapters(<span class="hljs-string">&quot;cinematic&quot;</span>)`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(g);var v=e(g,2),Hr=r(v);a(Hr,{name:"disable_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.disable_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L780",parameters:[]});var Hs=e(Hr,4);p(Hs,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.disable_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image
<span class="hljs-keyword">import</span> torch

pipeline = AutoPipelineForText2Image.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(
    <span class="hljs-string">&quot;jbilcke-hf/sdxl-cinematic-1&quot;</span>, weight_name=<span class="hljs-string">&quot;pytorch_lora_weights.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;cinematic&quot;</span>
)
pipeline.disable_lora()`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(v);var b=e(v,2),Kr=r(b);a(Kr,{name:"enable_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L810",parameters:[]});var Ks=e(Kr,4);p(Ks,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image
<span class="hljs-keyword">import</span> torch

pipeline = AutoPipelineForText2Image.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(
    <span class="hljs-string">&quot;jbilcke-hf/sdxl-cinematic-1&quot;</span>, weight_name=<span class="hljs-string">&quot;pytorch_lora_weights.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;cinematic&quot;</span>
)
pipeline.enable_lora()`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(b);var L=e(b,2),$s=r(L);a($s,{name:"enable_lora_hotswap",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L987",parameters:[{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap.target_rank",description:`<strong>target_rank</strong> (<code>int</code>) &#x2014;
The highest rank among all the adapters that will be loaded.`,name:"target_rank"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap.check_compiled",description:`<strong>check_compiled</strong> (<code>str</code>, <em>optional</em>, defaults to <code>&quot;error&quot;</code>) &#x2014;
How to handle a model that is already compiled. The check can return the following messages:
<ul>
<li>&#x201C;error&#x201D; (default): raise an error</li>
<li>&#x201C;warn&#x201D;: issue a warning</li>
<li>&#x201C;ignore&#x201D;: do nothing</li>
</ul>`,name:"check_compiled"}]}),s(2),o(L);var x=e(L,2),$r=r(x);a($r,{name:"fuse_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L536",parameters:[{name:"components",val:": list[str] | None = None"},{name:"lora_scale",val:": float = 1.0"},{name:"safe_fusing",val:": bool = False"},{name:"adapter_names",val:": list[str] | None = None"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.components",description:"<strong>components</strong> &#x2014; (<code>list[str]</code>): list of LoRA-injectable components to fuse the LoRAs into.",name:"components"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.lora_scale",description:`<strong>lora_scale</strong> (<code>float</code>, defaults to 1.0) &#x2014;
Controls how much to influence the outputs with the LoRA parameters.`,name:"lora_scale"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.safe_fusing",description:`<strong>safe_fusing</strong> (<code>bool</code>, defaults to <code>False</code>) &#x2014;
Whether to check fused weights for NaN values before fusing and if values are NaN not fusing them.`,name:"safe_fusing"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.adapter_names",description:`<strong>adapter_names</strong> (<code>list[str]</code>, <em>optional</em>) &#x2014;
Adapter names to be used for fusing. If nothing is passed, all active adapters will be fused.`,name:"adapter_names"}]});var Os=e($r,4);p(Os,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
<span class="hljs-keyword">import</span> torch

pipeline = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(<span class="hljs-string">&quot;nerijs/pixel-art-xl&quot;</span>, weight_name=<span class="hljs-string">&quot;pixel-art-xl.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;pixel&quot;</span>)
pipeline.fuse_lora(lora_scale=<span class="hljs-number">0.7</span>)`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(x);var y=e(x,2),Or=r(y);a(Or,{name:"get_active_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_active_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L878",parameters:[]});var ei=e(Or,4);p(ei,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_active_adapters.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMERpZmZ1c2lvblBpcGVsaW5lJTBBJTBBcGlwZWxpbmUlMjAlM0QlMjBEaWZmdXNpb25QaXBlbGluZS5mcm9tX3ByZXRyYWluZWQoJTBBJTIwJTIwJTIwJTIwJTIyc3RhYmlsaXR5YWklMkZzdGFibGUtZGlmZnVzaW9uLXhsLWJhc2UtMS4wJTIyJTJDJTBBKS50byglMjJjdWRhJTIyKSUwQXBpcGVsaW5lLmxvYWRfbG9yYV93ZWlnaHRzKCUyMkNpcm9OMjAyMiUyRnRveS1mYWNlJTIyJTJDJTIwd2VpZ2h0X25hbWUlM0QlMjJ0b3lfZmFjZV9zZHhsLnNhZmV0ZW5zb3JzJTIyJTJDJTIwYWRhcHRlcl9uYW1lJTNEJTIydG95JTIyKSUwQXBpcGVsaW5lLmdldF9hY3RpdmVfYWRhcHRlcnMoKQ==",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>,
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(<span class="hljs-string">&quot;CiroN2022/toy-face&quot;</span>, weight_name=<span class="hljs-string">&quot;toy_face_sdxl.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;toy&quot;</span>)
pipeline.get_active_adapters()`,lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(y);var w=e(y,2),ai=r(w);a(ai,{name:"get_list_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_list_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L911",parameters:[]}),s(2),o(w);var M=e(w,2),eo=r(M);a(eo,{name:"set_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L677",parameters:[{name:"adapter_names",val:": list[str] | str"},{name:"adapter_weights",val:": float | dict | list[float] | list[dict] | None = None"}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters.adapter_names",description:`<strong>adapter_names</strong> (<code>list[str]</code> or <code>str</code>) &#x2014;
The names of the adapters to use.`,name:"adapter_names"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters.adapter_weights",description:`<strong>adapter_weights</strong> (<code>list[float, float]</code>, <em>optional</em>) &#x2014;
The adapter(s) weights to use with the UNet. If <code>None</code>, the weights are set to <code>1.0</code> for all the
adapters.`,name:"adapter_weights"}]});var ri=e(eo,4);p(ri,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image
<span class="hljs-keyword">import</span> torch

pipeline = AutoPipelineForText2Image.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(
    <span class="hljs-string">&quot;jbilcke-hf/sdxl-cinematic-1&quot;</span>, weight_name=<span class="hljs-string">&quot;pytorch_lora_weights.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;cinematic&quot;</span>
)
pipeline.load_lora_weights(<span class="hljs-string">&quot;nerijs/pixel-art-xl&quot;</span>, weight_name=<span class="hljs-string">&quot;pixel-art-xl.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;pixel&quot;</span>)
pipeline.set_adapters([<span class="hljs-string">&quot;cinematic&quot;</span>, <span class="hljs-string">&quot;pixel&quot;</span>], adapter_weights=[<span class="hljs-number">0.5</span>, <span class="hljs-number">0.5</span>])`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(M);var S=e(M,2),ao=r(S);a(ao,{name:"set_lora_device",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L933",parameters:[{name:"adapter_names",val:": list[str]"},{name:"device",val:": torch.device | str | int"}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device.adapter_names",description:`<strong>adapter_names</strong> (<code>list[str]</code>) &#x2014;
list of adapters to send device to.`,name:"adapter_names"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device.device",description:`<strong>device</strong> (<code>torch.device | str | int</code>) &#x2014;
Device to send the adapters to. Can be either a torch device, a str or an integer.`,name:"device"}]});var oi=e(ao,6);p(oi,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device.example",children:(t,n)=>{c(t,{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.load_lora_weights(path_1, adapter_name=<span class="hljs-string">&quot;adapter-1&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.load_lora_weights(path_2, adapter_name=<span class="hljs-string">&quot;adapter-2&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.set_adapters(<span class="hljs-string">&quot;adapter-1&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>image_1 = pipe(**kwargs)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># switch to adapter-2, offload adapter-1</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">&quot;adapter-1&quot;</span>], device=<span class="hljs-string">&quot;cpu&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">&quot;adapter-2&quot;</span>], device=<span class="hljs-string">&quot;cuda:0&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.set_adapters(<span class="hljs-string">&quot;adapter-2&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>image_2 = pipe(**kwargs)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># switch back to adapter-1, offload adapter-2</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">&quot;adapter-2&quot;</span>], device=<span class="hljs-string">&quot;cpu&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">&quot;adapter-1&quot;</span>], device=<span class="hljs-string">&quot;cuda:0&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.set_adapters(<span class="hljs-string">&quot;adapter-1&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>...`,lang:"python",wrap:!1})},$$slots:{default:!0}}),o(S);var T=e(S,2),si=r(T);a(si,{name:"unfuse_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L623",parameters:[{name:"components",val:": list[str] | None = None"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora.components",description:"<strong>components</strong> (<code>list[str]</code>) &#x2014; list of LoRA-injectable components to unfuse LoRA from.",name:"components"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora.unfuse_unet",description:"<strong>unfuse_unet</strong> (<code>bool</code>, defaults to <code>True</code>) &#x2014; Whether to unfuse the UNet LoRA parameters.",name:"unfuse_unet"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora.unfuse_text_encoder",description:`<strong>unfuse_text_encoder</strong> (<code>bool</code>, defaults to <code>True</code>) &#x2014;
Whether to unfuse the text encoder LoRA parameters. If the text encoder wasn&#x2019;t monkey-patched with the
LoRA parameters then it won&#x2019;t have any effect.`,name:"unfuse_text_encoder"}]}),s(2),o(T);var N=e(T,2),ro=r(N);a(ro,{name:"unload_lora_weights",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unload_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L513",parameters:[]});var ii=e(ro,4);p(ii,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unload_lora_weights.example",children:(t,n)=>{var i=Cr(),l=e(_(i),2);c(l,{code:"JTIzJTIwQXNzdW1pbmclMjAlNjBwaXBlbGluZSU2MCUyMGlzJTIwYWxyZWFkeSUyMGxvYWRlZCUyMHdpdGglMjB0aGUlMjBMb1JBJTIwcGFyYW1ldGVycy4lMEFwaXBlbGluZS51bmxvYWRfbG9yYV93ZWlnaHRzKCklMEEuLi4=",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Assuming `pipeline` is already loaded with the LoRA parameters.</span>\n<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.unload_lora_weights()\n<span class="hljs-meta">&gt;&gt;&gt; </span>...',lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(N);var oo=e(N,2),ti=r(oo);a(ti,{name:"write_lora_layers",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.write_lora_layers",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L1010",parameters:[{name:"state_dict",val:": dict[str, torch.Tensor]"},{name:"save_directory",val:": str"},{name:"is_main_process",val:": bool"},{name:"weight_name",val:": str"},{name:"save_function",val:": Callable"},{name:"safe_serialization",val:": bool"},{name:"lora_adapter_metadata",val:": dict | None = None"}]}),s(2),o(oo),o(h);var so=e(h,2);d(so,{title:"StableDiffusionLoraLoaderMixin",local:"diffusers.loaders.StableDiffusionLoraLoaderMixin",headingTag:"h2"});var k=e(so,2),io=r(k);a(io,{name:"class diffusers.loaders.StableDiffusionLoraLoaderMixin",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L137",parameters:[]});var R=e(io,4),di=r(R);a(di,{name:"load_lora_into_text_encoder",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L420",parameters:[{name:"state_dict",val:""},{name:"network_alphas",val:""},{name:"text_encoder",val:""},{name:"prefix",val:" = None"},{name:"lora_scale",val:" = 1.0"},{name:"adapter_name",val:" = None"},{name:"_pipeline",val:" = None"},{name:"low_cpu_mem_usage",val:" = False"},{name:"hotswap",val:": bool = False"},{name:"metadata",val:" = None"}],parametersDescription:[{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.state_dict",description:`<strong>state_dict</strong> (<code>dict</code>) &#x2014;
A standard state dict containing the lora layer parameters. The key should be prefixed with an
additional <code>text_encoder</code> to distinguish between unet lora layers.`,name:"state_dict"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.network_alphas",description:`<strong>network_alphas</strong> (<code>dict[str, float]</code>) &#x2014;
The value of the network alpha used for stable learning and preventing underflow. This value has the
same meaning as the <code>--network_alpha</code> option in the kohya-ss trainer script. Refer to <a href="https://github.com/darkstorm2150/sd-scripts/blob/main/docs/train_network_README-en.md#execute-learning" rel="nofollow">this
link</a>.`,name:"network_alphas"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.text_encoder",description:`<strong>text_encoder</strong> (<code>CLIPTextModel</code>) &#x2014;
The text encoder model to load the LoRA layers into.`,name:"text_encoder"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.prefix",description:`<strong>prefix</strong> (<code>str</code>) &#x2014;
Expected prefix of the <code>text_encoder</code> in the <code>state_dict</code>.`,name:"prefix"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.lora_scale",description:`<strong>lora_scale</strong> (<code>float</code>) &#x2014;
How much to scale the output of the lora linear layer before it is added with the output of the regular
lora layer.`,name:"lora_scale"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.adapter_name",description:`<strong>adapter_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
<code>default_{i}</code> where i is the total number of adapters being loaded.`,name:"adapter_name"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.low_cpu_mem_usage",description:`<strong>low_cpu_mem_usage</strong> (<code>bool</code>, <em>optional</em>) &#x2014;
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.`,name:"low_cpu_mem_usage"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.hotswap",description:`<strong>hotswap</strong> (<code>bool</code>, <em>optional</em>) &#x2014;
See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a>.`,name:"hotswap"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder.metadata",description:`<strong>metadata</strong> (<code>dict</code>) &#x2014;
Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won&#x2019;t be derived
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The value of the network alpha used for stable learning and preventing underflow. This value has the
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See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict">lora_state_dict()</a>.`,name:"pretrained_model_name_or_path_or_dict"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights.adapter_name",description:`<strong>adapter_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
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Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
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Defaults to <code>False</code>. Whether to substitute an existing (LoRA) adapter with the newly loaded adapter
in-place. This means that, instead of loading an additional adapter, this will take the existing
adapter weights and replace them with the weights of the new adapter. This can be faster and more
memory efficient. However, the main advantage of hotswapping is that when the model is compiled with
torch.compile, loading the new adapter does not require recompilation of the model. When using
hotswapping, the passed <code>adapter_name</code> should be the name of an already loaded adapter.</p>
<p>If the new adapter and the old adapter have different ranks and/or LoRA alphas (i.e. scaling), you need
to call an additional method before loading the adapter:`,name:"hotswap"}]}),s(10),o(J);var D=e(J,2),ci=r(D);a(ci,{name:"lora_state_dict",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L248",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict.pretrained_model_name_or_path_or_dict",description:`<strong>pretrained_model_name_or_path_or_dict</strong> (<code>str</code> or <code>os.PathLike</code> or <code>dict</code>) &#x2014;
Can be either:</p>
<ul>
<li>A string, the <em>model id</em> (for example <code>google/ddpm-celebahq-256</code>) of a pretrained model hosted on
the Hub.</li>
<li>A path to a <em>directory</em> (for example <code>./my_model_directory</code>) containing the model weights saved
with <a href="/docs/diffusers/pr_14358/en/api/models/overview#diffusers.ModelMixin.save_pretrained">ModelMixin.save_pretrained()</a>.</li>
<li>A <a href="https://pytorch.org/tutorials/beginner/saving_loading_models.html#what-is-a-state-dict" rel="nofollow">torch state
dict</a>.</li>
</ul>`,name:"pretrained_model_name_or_path_or_dict"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict.cache_dir",description:`<strong>cache_dir</strong> (<code>str | os.PathLike</code>, <em>optional</em>) &#x2014;
Path to a directory where a downloaded pretrained model configuration is cached if the standard cache
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Whether or not to force the (re-)download of the model weights and configuration files, overriding the
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A dictionary of proxy servers to use by protocol or endpoint, for example, <code>{&apos;http&apos;: &apos;foo.bar:3128&apos;, &apos;http://hostname&apos;: &apos;foo.bar:4012&apos;}</code>. The proxies are used on each request.`,name:"proxies"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict.local_files_only",description:`<strong>local_files_only</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>False</code>) &#x2014;
Whether to only load local model weights and configuration files or not. If set to <code>True</code>, the model
won&#x2019;t be downloaded from the Hub.`,name:"local_files_only"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict.token",description:`<strong>token</strong> (<code>str</code> or <em>bool</em>, <em>optional</em>) &#x2014;
The token to use as HTTP bearer authorization for remote files. If <code>True</code>, the token generated from
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The specific model version to use. It can be a branch name, a tag name, a commit id, or any identifier
allowed by Git.`,name:"revision"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict.subfolder",description:`<strong>subfolder</strong> (<code>str</code>, <em>optional</em>, defaults to <code>&quot;&quot;</code>) &#x2014;
The subfolder location of a model file within a larger model repository on the Hub or locally.`,name:"subfolder"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict.weight_name",description:`<strong>weight_name</strong> (<code>str</code>, <em>optional</em>, defaults to None) &#x2014;
Name of the serialized state dict file.`,name:"weight_name"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict.return_lora_metadata",description:`<strong>return_lora_metadata</strong> (<code>bool</code>, <em>optional</em>, defaults to False) &#x2014;
When enabled, additionally return the LoRA adapter metadata, typically found in the state dict.`,name:"return_lora_metadata"}]}),s(4),o(D);var to=e(D,2),fi=r(to);a(fi,{name:"save_lora_weights",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L478",parameters:[{name:"save_directory",val:": str | os.PathLike"},{name:"unet_lora_layers",val:": dict = None"},{name:"text_encoder_lora_layers",val:": dict = None"},{name:"is_main_process",val:": bool = True"},{name:"weight_name",val:": str = None"},{name:"save_function",val:": typing.Callable = None"},{name:"safe_serialization",val:": bool = True"},{name:"unet_lora_adapter_metadata",val:" = None"},{name:"text_encoder_lora_adapter_metadata",val:" = None"}],parametersDescription:[{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights.save_directory",description:`<strong>save_directory</strong> (<code>str</code> or <code>os.PathLike</code>) &#x2014;
Directory to save LoRA parameters to. Will be created if it doesn&#x2019;t exist.`,name:"save_directory"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights.unet_lora_layers",description:`<strong>unet_lora_layers</strong> (<code>dict[str, torch.nn.Module]</code> or <code>dict[str, torch.Tensor]</code>) &#x2014;
State dict of the LoRA layers corresponding to the <code>unet</code>.`,name:"unet_lora_layers"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights.text_encoder_lora_layers",description:`<strong>text_encoder_lora_layers</strong> (<code>dict[str, torch.nn.Module]</code> or <code>dict[str, torch.Tensor]</code>) &#x2014;
State dict of the LoRA layers corresponding to the <code>text_encoder</code>. Must explicitly pass the text
encoder LoRA state dict because it comes from &#x1F917; Transformers.`,name:"text_encoder_lora_layers"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights.is_main_process",description:`<strong>is_main_process</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) &#x2014;
Whether the process calling this is the main process or not. Useful during distributed training and you
need to call this function on all processes. In this case, set <code>is_main_process=True</code> only on the main
process to avoid race conditions.`,name:"is_main_process"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights.save_function",description:`<strong>save_function</strong> (<code>Callable</code>) &#x2014;
The function to use to save the state dictionary. Useful during distributed training when you need to
replace <code>torch.save</code> with another method. Can be configured with the environment variable
<code>DIFFUSERS_SAVE_MODE</code>.`,name:"save_function"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights.safe_serialization",description:`<strong>safe_serialization</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) &#x2014;
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LoRA adapter metadata associated with the unet to be serialized with the state dict.`,name:"unet_lora_adapter_metadata"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights.text_encoder_lora_adapter_metadata",description:`<strong>text_encoder_lora_adapter_metadata</strong> &#x2014;
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A standard state dict containing the lora layer parameters. The key should be prefixed with an
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The value of the network alpha used for stable learning and preventing underflow. This value has the
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How much to scale the output of the lora linear layer before it is added with the output of the regular
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Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
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Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
weights.`,name:"low_cpu_mem_usage"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.hotswap",description:`<strong>hotswap</strong> (<code>bool</code>, <em>optional</em>) &#x2014;
See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a>.`,name:"hotswap"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.metadata",description:`<strong>metadata</strong> (<code>dict</code>) &#x2014;
Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won&#x2019;t be derived
from the state dict.`,name:"metadata"}]}),s(2),o(X);var j=e(X,2),mi=r(j);a(mi,{name:"load_lora_into_unet",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L794",parameters:[{name:"state_dict",val:""},{name:"network_alphas",val:""},{name:"unet",val:""},{name:"adapter_name",val:" = None"},{name:"_pipeline",val:" = None"},{name:"low_cpu_mem_usage",val:" = False"},{name:"hotswap",val:": bool = False"},{name:"metadata",val:" = None"}],parametersDescription:[{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet.state_dict",description:`<strong>state_dict</strong> (<code>dict</code>) &#x2014;
A standard state dict containing the lora layer parameters. The keys can either be indexed directly
into the unet or prefixed with an additional <code>unet</code> which can be used to distinguish between text
encoder lora layers.`,name:"state_dict"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet.network_alphas",description:`<strong>network_alphas</strong> (<code>dict[str, float]</code>) &#x2014;
The value of the network alpha used for stable learning and preventing underflow. This value has the
same meaning as the <code>--network_alpha</code> option in the kohya-ss trainer script. Refer to <a href="https://github.com/darkstorm2150/sd-scripts/blob/main/docs/train_network_README-en.md#execute-learning" rel="nofollow">this
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Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
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See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a>.`,name:"hotswap"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet.metadata",description:`<strong>metadata</strong> (<code>dict</code>) &#x2014;
Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won&#x2019;t be derived
from the state dict.`,name:"metadata"}]}),s(2),o(j);var I=e(j,2),ui=r(I);a(ui,{name:"load_lora_weights",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L608",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"adapter_name",val:": str | None = None"},{name:"hotswap",val:": bool = False"},{name:"**kwargs",val:""}]}),s(2),o(I);var G=e(I,2),hi=r(G);a(hi,{name:"lora_state_dict",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L682",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.pretrained_model_name_or_path_or_dict",description:`<strong>pretrained_model_name_or_path_or_dict</strong> (<code>str</code> or <code>os.PathLike</code> or <code>dict</code>) &#x2014;
Can be either:</p>
<ul>
<li>A string, the <em>model id</em> (for example <code>google/ddpm-celebahq-256</code>) of a pretrained model hosted on
the Hub.</li>
<li>A path to a <em>directory</em> (for example <code>./my_model_directory</code>) containing the model weights saved
with <a href="/docs/diffusers/pr_14358/en/api/models/overview#diffusers.ModelMixin.save_pretrained">ModelMixin.save_pretrained()</a>.</li>
<li>A <a href="https://pytorch.org/tutorials/beginner/saving_loading_models.html#what-is-a-state-dict" rel="nofollow">torch state
dict</a>.</li>
</ul>`,name:"pretrained_model_name_or_path_or_dict"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.cache_dir",description:`<strong>cache_dir</strong> (<code>str | os.PathLike</code>, <em>optional</em>) &#x2014;
Path to a directory where a downloaded pretrained model configuration is cached if the standard cache
is not used.`,name:"cache_dir"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.force_download",description:`<strong>force_download</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>False</code>) &#x2014;
Whether or not to force the (re-)download of the model weights and configuration files, overriding the
cached versions if they exist.`,name:"force_download"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.proxies",description:`<strong>proxies</strong> (<code>dict[str, str]</code>, <em>optional</em>) &#x2014;
A dictionary of proxy servers to use by protocol or endpoint, for example, <code>{&apos;http&apos;: &apos;foo.bar:3128&apos;, &apos;http://hostname&apos;: &apos;foo.bar:4012&apos;}</code>. The proxies are used on each request.`,name:"proxies"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.local_files_only",description:`<strong>local_files_only</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>False</code>) &#x2014;
Whether to only load local model weights and configuration files or not. If set to <code>True</code>, the model
won&#x2019;t be downloaded from the Hub.`,name:"local_files_only"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.token",description:`<strong>token</strong> (<code>str</code> or <em>bool</em>, <em>optional</em>) &#x2014;
The token to use as HTTP bearer authorization for remote files. If <code>True</code>, the token generated from
<code>diffusers-cli login</code> (stored in <code>~/.huggingface</code>) is used.`,name:"token"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>, defaults to <code>&quot;main&quot;</code>) &#x2014;
The specific model version to use. It can be a branch name, a tag name, a commit id, or any identifier
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The subfolder location of a model file within a larger model repository on the Hub or locally.`,name:"subfolder"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.weight_name",description:`<strong>weight_name</strong> (<code>str</code>, <em>optional</em>, defaults to None) &#x2014;
Name of the serialized state dict file.`,name:"weight_name"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict.return_lora_metadata",description:`<strong>return_lora_metadata</strong> (<code>bool</code>, <em>optional</em>, defaults to False) &#x2014;
When enabled, additionally return the LoRA adapter metadata, typically found in the state dict.`,name:"return_lora_metadata"}]}),s(4),o(G);var W=e(G,2),gi=r(W);a(gi,{name:"save_lora_weights",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L915",parameters:[{name:"save_directory",val:": str | os.PathLike"},{name:"unet_lora_layers",val:": dict = None"},{name:"text_encoder_lora_layers",val:": dict = None"},{name:"text_encoder_2_lora_layers",val:": dict = None"},{name:"is_main_process",val:": bool = True"},{name:"weight_name",val:": str = None"},{name:"save_function",val:": typing.Callable = None"},{name:"safe_serialization",val:": bool = True"},{name:"unet_lora_adapter_metadata",val:" = None"},{name:"text_encoder_lora_adapter_metadata",val:" = None"},{name:"text_encoder_2_lora_adapter_metadata",val:" = None"}]}),s(2),o(W);var co=e(W,2),vi=r(co);a(vi,{name:"unfuse_lora",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L982",parameters:[{name:"components",val:": list = ['unet', 'text_encoder', 'text_encoder_2']"},{name:"**kwargs",val:""}]}),s(2),o(co),o(Z);var fo=e(Z,2);d(fo,{title:"SD3LoraLoaderMixin",local:"diffusers.loaders.SD3LoraLoaderMixin",headingTag:"h2"});var B=e(fo,2),po=r(B);a(po,{name:"class diffusers.loaders.SD3LoraLoaderMixin",anchor:"diffusers.loaders.SD3LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L989",parameters:[]});var V=e(po,6),bi=r(V);a(bi,{name:"fuse_lora",anchor:"diffusers.loaders.SD3LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L1261",parameters:[{name:"components",val:": list = ['transformer', 'text_encoder', 'text_encoder_2']"},{name:"lora_scale",val:": float = 1.0"},{name:"safe_fusing",val:": bool = False"},{name:"adapter_names",val:": list[str] | None = None"},{name:"**kwargs",val:""}]}),s(2),o(V);var A=e(V,2),Li=r(A);a(Li,{name:"load_lora_into_text_encoder",anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L1152",parameters:[{name:"state_dict",val:""},{name:"network_alphas",val:""},{name:"text_encoder",val:""},{name:"prefix",val:" = None"},{name:"lora_scale",val:" = 1.0"},{name:"adapter_name",val:" = None"},{name:"_pipeline",val:" = None"},{name:"low_cpu_mem_usage",val:" = False"},{name:"hotswap",val:": bool = False"},{name:"metadata",val:" = None"}],parametersDescription:[{anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder.state_dict",description:`<strong>state_dict</strong> (<code>dict</code>) &#x2014;
A standard state dict containing the lora layer parameters. The key should be prefixed with an
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The value of the network alpha used for stable learning and preventing underflow. This value has the
same meaning as the <code>--network_alpha</code> option in the kohya-ss trainer script. Refer to <a href="https://github.com/darkstorm2150/sd-scripts/blob/main/docs/train_network_README-en.md#execute-learning" rel="nofollow">this
link</a>.`,name:"network_alphas"},{anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder.text_encoder",description:`<strong>text_encoder</strong> (<code>CLIPTextModel</code>) &#x2014;
The text encoder model to load the LoRA layers into.`,name:"text_encoder"},{anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder.prefix",description:`<strong>prefix</strong> (<code>str</code>) &#x2014;
Expected prefix of the <code>text_encoder</code> in the <code>state_dict</code>.`,name:"prefix"},{anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder.lora_scale",description:`<strong>lora_scale</strong> (<code>float</code>) &#x2014;
How much to scale the output of the lora linear layer before it is added with the output of the regular
lora layer.`,name:"lora_scale"},{anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder.adapter_name",description:`<strong>adapter_name</strong> (<code>str</code>, <em>optional</em>) &#x2014;
Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
<code>default_{i}</code> where i is the total number of adapters being loaded.`,name:"adapter_name"},{anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder.low_cpu_mem_usage",description:`<strong>low_cpu_mem_usage</strong> (<code>bool</code>, <em>optional</em>) &#x2014;
Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
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See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a>.`,name:"hotswap"},{anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder.metadata",description:`<strong>metadata</strong> (<code>dict</code>) &#x2014;
Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won&#x2019;t be derived
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A standard state dict containing the lora layer parameters. The key should be prefixed with an
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The value of the network alpha used for stable learning and preventing underflow. This value has the
same meaning as the <code>--network_alpha</code> option in the kohya-ss trainer script. Refer to <a href="https://github.com/darkstorm2150/sd-scripts/blob/main/docs/train_network_README-en.md#execute-learning" rel="nofollow">this
link</a>.`,name:"network_alphas"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.load_lora_into_text_encoder.text_encoder",description:`<strong>text_encoder</strong> (<code>CLIPTextModel</code>) &#x2014;
The text encoder model to load the LoRA layers into.`,name:"text_encoder"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.load_lora_into_text_encoder.prefix",description:`<strong>prefix</strong> (<code>str</code>) &#x2014;
Expected prefix of the <code>text_encoder</code> in the <code>state_dict</code>.`,name:"prefix"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.load_lora_into_text_encoder.lora_scale",description:`<strong>lora_scale</strong> (<code>float</code>) &#x2014;
How much to scale the output of the lora linear layer before it is added with the output of the regular
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Adapter name to be used for referencing the loaded adapter model. If not specified, it will use
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Speed up model loading by only loading the pretrained LoRA weights and not initializing the random
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See <a href="/docs/diffusers/pr_14358/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a>.`,name:"hotswap"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.load_lora_into_text_encoder.metadata",description:`<strong>metadata</strong> (<code>dict</code>) &#x2014;
Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won&#x2019;t be derived
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State dict of the LoRA layers corresponding to the <code>transformer</code>.`,name:"transformer_lora_layers"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights.text_encoder_lora_layers",description:`<strong>text_encoder_lora_layers</strong> (<code>dict[str, torch.nn.Module]</code> or <code>dict[str, torch.Tensor]</code>) &#x2014;
State dict of the LoRA layers corresponding to the <code>text_encoder</code>. Must explicitly pass the text
encoder LoRA state dict because it comes from &#x1F917; Transformers.`,name:"text_encoder_lora_layers"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights.is_main_process",description:`<strong>is_main_process</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) &#x2014;
Whether the process calling this is the main process or not. Useful during distributed training and you
need to call this function on all processes. In this case, set <code>is_main_process=True</code> only on the main
process to avoid race conditions.`,name:"is_main_process"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights.save_function",description:`<strong>save_function</strong> (<code>Callable</code>) &#x2014;
The function to use to save the state dictionary. Useful during distributed training when you need to
replace <code>torch.save</code> with another method. Can be configured with the environment variable
<code>DIFFUSERS_SAVE_MODE</code>.`,name:"save_function"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights.safe_serialization",description:`<strong>safe_serialization</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) &#x2014;
Whether to save the model using <code>safetensors</code> or the traditional PyTorch way with <code>pickle</code>.`,name:"safe_serialization"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights.transformer_lora_adapter_metadata",description:`<strong>transformer_lora_adapter_metadata</strong> &#x2014;
LoRA adapter metadata associated with the transformer to be serialized with the state dict.`,name:"transformer_lora_adapter_metadata"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights.text_encoder_lora_adapter_metadata",description:`<strong>text_encoder_lora_adapter_metadata</strong> &#x2014;
LoRA adapter metadata associated with the text encoder to be serialized with the state dict.`,name:"text_encoder_lora_adapter_metadata"}]}),s(2),o(O);var ee=e(O,2),Di=r(ee);a(Di,{name:"unfuse_lora",anchor:"diffusers.loaders.FluxLoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L1969",parameters:[{name:"components",val:": list = ['transformer', 'text_encoder']"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.FluxLoraLoaderMixin.unfuse_lora.components",description:"<strong>components</strong> (<code>list[str]</code>) &#x2014; list of LoRA-injectable components to unfuse LoRA from.",name:"components"}]}),s(2),o(ee);var ho=e(ee,2),go=r(ho);a(go,{name:"unload_lora_weights",anchor:"diffusers.loaders.FluxLoraLoaderMixin.unload_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L1984",parameters:[{name:"reset_to_overwritten_params",val:" = False"}],parametersDescription:[{anchor:"diffusers.loaders.FluxLoraLoaderMixin.unload_lora_weights.reset_to_overwritten_params",description:`<strong>reset_to_overwritten_params</strong> (<code>bool</code>, defaults to <code>False</code>) &#x2014; Whether to reset the LoRA-loaded modules
to their original params. Refer to the <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux" rel="nofollow">Flux
documentation</a> to learn more.`,name:"reset_to_overwritten_params"}]});var Zi=e(go,4);p(Zi,{anchor:"diffusers.loaders.FluxLoraLoaderMixin.unload_lora_weights.example",children:(t,n)=>{var i=Cr(),l=e(_(i),2);c(l,{code:"JTIzJTIwQXNzdW1pbmclMjAlNjBwaXBlbGluZSU2MCUyMGlzJTIwYWxyZWFkeSUyMGxvYWRlZCUyMHdpdGglMjB0aGUlMjBMb1JBJTIwcGFyYW1ldGVycy4lMEFwaXBlbGluZS51bmxvYWRfbG9yYV93ZWlnaHRzKCklMEEuLi4=",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Assuming `pipeline` is already loaded with the LoRA parameters.</span>\n<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.unload_lora_weights()\n<span class="hljs-meta">&gt;&gt;&gt; </span>...',lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(ho),o(Q);var vo=e(Q,2);d(vo,{title:"Flux2LoraLoaderMixin",local:"diffusers.loaders.Flux2LoraLoaderMixin",headingTag:"h2"});var ae=e(vo,2),bo=r(ae);a(bo,{name:"class 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oe=e(re,2),Xi=r(oe);a(Xi,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L6128",parameters:[{name:"state_dict",val:""},{name:"transformer",val:""},{name:"adapter_name",val:" = None"},{name:"_pipeline",val:" = None"},{name:"low_cpu_mem_usage",val:" = False"},{name:"hotswap",val:": bool = False"},{name:"metadata",val:" = None"}]}),s(2),o(oe);var se=e(oe,2),ji=r(se);a(ji,{name:"load_lora_weights",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L6087",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"adapter_name",val:": str | None = None"},{name:"hotswap",val:": bool = False"},{name:"**kwargs",val:""}]}),s(2),o(se);var ie=e(se,2),Ii=r(ie);a(Ii,{name:"lora_state_dict",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L6017",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(ie);var te=e(ie,2),Gi=r(te);a(Gi,{name:"save_lora_weights",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L6160",parameters:[{name:"save_directory",val:": str | os.PathLike"},{name:"transformer_lora_layers",val:": dict = None"},{name:"is_main_process",val:": bool = True"},{name:"weight_name",val:": str = None"},{name:"save_function",val:": typing.Callable = None"},{name:"safe_serialization",val:": bool = True"},{name:"transformer_lora_adapter_metadata",val:": dict | None = None"}]}),s(2),o(te);var 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ce=e(ne,2),Ai=r(ce);a(Ai,{name:"load_lora_weights",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L6505",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"adapter_name",val:": str | None = None"},{name:"hotswap",val:": bool = False"},{name:"**kwargs",val:""}]}),s(2),o(ce);var fe=e(ce,2),Ci=r(fe);a(Ci,{name:"lora_state_dict",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L6438",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(fe);var 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Mo=e(de,2);d(Mo,{title:"LTX2LoraLoaderMixin",local:"diffusers.loaders.LTX2LoraLoaderMixin",headingTag:"h2"});var _e=e(Mo,2),So=r(_e);a(So,{name:"class diffusers.loaders.LTX2LoraLoaderMixin",anchor:"diffusers.loaders.LTX2LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L3015",parameters:[]});var me=e(So,4),zi=r(me);a(zi,{name:"fuse_lora",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L3215",parameters:[{name:"components",val:": list = ['transformer']"},{name:"lora_scale",val:": float = 1.0"},{name:"safe_fusing",val:": bool = False"},{name:"adapter_names",val:": list[str] | None = None"},{name:"**kwargs",val:""}]}),s(2),o(me);var ue=e(me,2),Qi=r(ue);a(Qi,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L3146",parameters:[{name:"state_dict",val:""},{name:"transformer",val:""},{name:"adapter_name",val:" = None"},{name:"_pipeline",val:" = None"},{name:"low_cpu_mem_usage",val:" = False"},{name:"hotswap",val:": bool = False"},{name:"metadata",val:" = None"},{name:"prefix",val:": str = 'transformer'"}]}),s(2),o(ue);var he=e(ue,2),Pi=r(he);a(Pi,{name:"load_lora_weights",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L3088",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"adapter_name",val:": str | None = None"},{name:"hotswap",val:": bool = 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ye=e(xe,2),et=r(ye);a(et,{name:"load_lora_weights",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2479",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"adapter_name",val:": str | None = None"},{name:"hotswap",val:": bool = False"},{name:"**kwargs",val:""}]}),s(2),o(ye);var we=e(ye,2),at=r(we);a(at,{name:"lora_state_dict",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2424",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(we);var 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Uo=e(be,2);d(Uo,{title:"Mochi1LoraLoaderMixin",local:"diffusers.loaders.Mochi1LoraLoaderMixin",headingTag:"h2"});var Se=e(Uo,2),Jo=r(Se);a(Jo,{name:"class diffusers.loaders.Mochi1LoraLoaderMixin",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2612",parameters:[]});var Te=e(Jo,4),st=r(Te);a(st,{name:"fuse_lora",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2785",parameters:[{name:"components",val:": list = ['transformer']"},{name:"lora_scale",val:": float = 1.0"},{name:"safe_fusing",val:": bool = False"},{name:"adapter_names",val:": list[str] | None = None"},{name:"**kwargs",val:""}]}),s(2),o(Te);var Ne=e(Te,2),it=r(Ne);a(it,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2717",parameters:[{name:"state_dict",val:""},{name:"transformer",val:""},{name:"adapter_name",val:" = None"},{name:"_pipeline",val:" = None"},{name:"low_cpu_mem_usage",val:" = False"},{name:"hotswap",val:": bool = False"},{name:"metadata",val:" = None"}]}),s(2),o(Ne);var ke=e(Ne,2),tt=r(ke);a(tt,{name:"load_lora_weights",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2676",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"adapter_name",val:": str | None = None"},{name:"hotswap",val:": bool = False"},{name:"**kwargs",val:""}]}),s(2),o(ke);var Re=e(ke,2),dt=r(Re);a(dt,{name:"lora_state_dict",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2620",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(Re);var Ue=e(Re,2),lt=r(Ue);a(lt,{name:"save_lora_weights",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2749",parameters:[{name:"save_directory",val:": str | os.PathLike"},{name:"transformer_lora_layers",val:": dict = None"},{name:"is_main_process",val:": bool = True"},{name:"weight_name",val:": str = None"},{name:"save_function",val:": typing.Callable = None"},{name:"safe_serialization",val:": bool = True"},{name:"transformer_lora_adapter_metadata",val:": dict | None = None"}]}),s(2),o(Ue);var Do=e(Ue,2),nt=r(Do);a(nt,{name:"unfuse_lora",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L2805",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(Do),o(Se);var Zo=e(Se,2);d(Zo,{title:"AuraFlowLoraLoaderMixin",local:"diffusers.loaders.AuraFlowLoraLoaderMixin",headingTag:"h2"});var Je=e(Zo,2),Fo=r(Je);a(Fo,{name:"class diffusers.loaders.AuraFlowLoraLoaderMixin",anchor:"diffusers.loaders.AuraFlowLoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L1288",parameters:[]});var De=e(Fo,4),ct=r(De);a(ct,{name:"fuse_lora",anchor:"diffusers.loaders.AuraFlowLoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L1461",parameters:[{name:"components",val:": list = 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None"},{name:"safe_serialization",val:": bool = True"},{name:"transformer_lora_adapter_metadata",val:": dict | None = None"}]}),s(2),o(Ur);var Xs=e(Ur,2),nl=r(Xs);a(nl,{name:"unfuse_lora",anchor:"diffusers.loaders.Krea2LoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_pipeline.py#L5608",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(Xs),o(Sr);var js=e(Sr,2);d(js,{title:"LoraBaseMixin",local:"diffusers.loaders.lora_base.LoraBaseMixin",headingTag:"h2"});var Jr=e(js,2),Is=r(Jr);a(Is,{name:"class diffusers.loaders.lora_base.LoraBaseMixin",anchor:"diffusers.loaders.lora_base.LoraBaseMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L478",parameters:[]});var Dr=e(Is,4),Gs=r(Dr);a(Gs,{name:"delete_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L840",parameters:[{name:"adapter_names",val:": list[str] | str"}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters.adapter_names",description:`<strong>adapter_names</strong> (<code>list[str, str]</code>) &#x2014;
The names of the adapters to delete.`,name:"adapter_names"}]});var cl=e(Gs,4);p(cl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image
<span class="hljs-keyword">import</span> torch

pipeline = AutoPipelineForText2Image.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(
    <span class="hljs-string">&quot;jbilcke-hf/sdxl-cinematic-1&quot;</span>, weight_name=<span class="hljs-string">&quot;pytorch_lora_weights.safetensors&quot;</span>, adapter_names=<span class="hljs-string">&quot;cinematic&quot;</span>
)
pipeline.delete_adapters(<span class="hljs-string">&quot;cinematic&quot;</span>)`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Dr);var Zr=e(Dr,2),Ws=r(Zr);a(Ws,{name:"disable_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.disable_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L780",parameters:[]});var fl=e(Ws,4);p(fl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.disable_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image
<span class="hljs-keyword">import</span> torch

pipeline = AutoPipelineForText2Image.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(
    <span class="hljs-string">&quot;jbilcke-hf/sdxl-cinematic-1&quot;</span>, weight_name=<span class="hljs-string">&quot;pytorch_lora_weights.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;cinematic&quot;</span>
)
pipeline.disable_lora()`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Zr);var Fr=e(Zr,2),Bs=r(Fr);a(Bs,{name:"enable_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L810",parameters:[]});var pl=e(Bs,4);p(pl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMEF1dG9QaXBlbGluZUZvclRleHQySW1hZ2UlMEFpbXBvcnQlMjB0b3JjaCUwQSUwQXBpcGVsaW5lJTIwJTNEJTIwQXV0b1BpcGVsaW5lRm9yVGV4dDJJbWFnZS5mcm9tX3ByZXRyYWluZWQoJTBBJTIwJTIwJTIwJTIwJTIyc3RhYmlsaXR5YWklMkZzdGFibGUtZGlmZnVzaW9uLXhsLWJhc2UtMS4wJTIyJTJDJTIwdG9yY2hfZHR5cGUlM0R0b3JjaC5mbG9hdDE2JTBBKS50byglMjJjdWRhJTIyKSUwQXBpcGVsaW5lLmxvYWRfbG9yYV93ZWlnaHRzKCUwQSUyMCUyMCUyMCUyMCUyMmpiaWxja2UtaGYlMkZzZHhsLWNpbmVtYXRpYy0xJTIyJTJDJTIwd2VpZ2h0X25hbWUlM0QlMjJweXRvcmNoX2xvcmFfd2VpZ2h0cy5zYWZldGVuc29ycyUyMiUyQyUyMGFkYXB0ZXJfbmFtZSUzRCUyMmNpbmVtYXRpYyUyMiUwQSklMEFwaXBlbGluZS5lbmFibGVfbG9yYSgp",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image
<span class="hljs-keyword">import</span> torch

pipeline = AutoPipelineForText2Image.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(
    <span class="hljs-string">&quot;jbilcke-hf/sdxl-cinematic-1&quot;</span>, weight_name=<span class="hljs-string">&quot;pytorch_lora_weights.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;cinematic&quot;</span>
)
pipeline.enable_lora()`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Fr);var Xr=e(Fr,2),_l=r(Xr);a(_l,{name:"enable_lora_hotswap",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L987",parameters:[{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap.target_rank",description:`<strong>target_rank</strong> (<code>int</code>) &#x2014;
The highest rank among all the adapters that will be loaded.`,name:"target_rank"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap.check_compiled",description:`<strong>check_compiled</strong> (<code>str</code>, <em>optional</em>, defaults to <code>&quot;error&quot;</code>) &#x2014;
How to handle a model that is already compiled. The check can return the following messages:
<ul>
<li>&#x201C;error&#x201D; (default): raise an error</li>
<li>&#x201C;warn&#x201D;: issue a warning</li>
<li>&#x201C;ignore&#x201D;: do nothing</li>
</ul>`,name:"check_compiled"}]}),s(2),o(Xr);var jr=e(Xr,2),Vs=r(jr);a(Vs,{name:"fuse_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L536",parameters:[{name:"components",val:": list[str] | None = None"},{name:"lora_scale",val:": float = 1.0"},{name:"safe_fusing",val:": bool = False"},{name:"adapter_names",val:": list[str] | None = None"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.components",description:"<strong>components</strong> &#x2014; (<code>list[str]</code>): list of LoRA-injectable components to fuse the LoRAs into.",name:"components"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.lora_scale",description:`<strong>lora_scale</strong> (<code>float</code>, defaults to 1.0) &#x2014;
Controls how much to influence the outputs with the LoRA parameters.`,name:"lora_scale"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.safe_fusing",description:`<strong>safe_fusing</strong> (<code>bool</code>, defaults to <code>False</code>) &#x2014;
Whether to check fused weights for NaN values before fusing and if values are NaN not fusing them.`,name:"safe_fusing"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.adapter_names",description:`<strong>adapter_names</strong> (<code>list[str]</code>, <em>optional</em>) &#x2014;
Adapter names to be used for fusing. If nothing is passed, all active adapters will be fused.`,name:"adapter_names"}]});var ml=e(Vs,4);p(ml,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline
<span class="hljs-keyword">import</span> torch

pipeline = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(<span class="hljs-string">&quot;nerijs/pixel-art-xl&quot;</span>, weight_name=<span class="hljs-string">&quot;pixel-art-xl.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;pixel&quot;</span>)
pipeline.fuse_lora(lora_scale=<span class="hljs-number">0.7</span>)`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(jr);var Ir=e(jr,2),As=r(Ir);a(As,{name:"get_active_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_active_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L878",parameters:[]});var ul=e(As,4);p(ul,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_active_adapters.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMERpZmZ1c2lvblBpcGVsaW5lJTBBJTBBcGlwZWxpbmUlMjAlM0QlMjBEaWZmdXNpb25QaXBlbGluZS5mcm9tX3ByZXRyYWluZWQoJTBBJTIwJTIwJTIwJTIwJTIyc3RhYmlsaXR5YWklMkZzdGFibGUtZGlmZnVzaW9uLXhsLWJhc2UtMS4wJTIyJTJDJTBBKS50byglMjJjdWRhJTIyKSUwQXBpcGVsaW5lLmxvYWRfbG9yYV93ZWlnaHRzKCUyMkNpcm9OMjAyMiUyRnRveS1mYWNlJTIyJTJDJTIwd2VpZ2h0X25hbWUlM0QlMjJ0b3lfZmFjZV9zZHhsLnNhZmV0ZW5zb3JzJTIyJTJDJTIwYWRhcHRlcl9uYW1lJTNEJTIydG95JTIyKSUwQXBpcGVsaW5lLmdldF9hY3RpdmVfYWRhcHRlcnMoKQ==",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>,
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(<span class="hljs-string">&quot;CiroN2022/toy-face&quot;</span>, weight_name=<span class="hljs-string">&quot;toy_face_sdxl.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;toy&quot;</span>)
pipeline.get_active_adapters()`,lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Ir);var Gr=e(Ir,2),hl=r(Gr);a(hl,{name:"get_list_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_list_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L911",parameters:[]}),s(2),o(Gr);var Wr=e(Gr,2),Cs=r(Wr);a(Cs,{name:"set_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L677",parameters:[{name:"adapter_names",val:": list[str] | str"},{name:"adapter_weights",val:": float | dict | list[float] | list[dict] | None = None"}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters.adapter_names",description:`<strong>adapter_names</strong> (<code>list[str]</code> or <code>str</code>) &#x2014;
The names of the adapters to use.`,name:"adapter_names"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters.adapter_weights",description:`<strong>adapter_weights</strong> (<code>list[float, float]</code>, <em>optional</em>) &#x2014;
The adapter(s) weights to use with the UNet. If <code>None</code>, the weights are set to <code>1.0</code> for all the
adapters.`,name:"adapter_weights"}]});var gl=e(Cs,4);p(gl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image
<span class="hljs-keyword">import</span> torch

pipeline = AutoPipelineForText2Image.from_pretrained(
    <span class="hljs-string">&quot;stabilityai/stable-diffusion-xl-base-1.0&quot;</span>, torch_dtype=torch.float16
).to(<span class="hljs-string">&quot;cuda&quot;</span>)
pipeline.load_lora_weights(
    <span class="hljs-string">&quot;jbilcke-hf/sdxl-cinematic-1&quot;</span>, weight_name=<span class="hljs-string">&quot;pytorch_lora_weights.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;cinematic&quot;</span>
)
pipeline.load_lora_weights(<span class="hljs-string">&quot;nerijs/pixel-art-xl&quot;</span>, weight_name=<span class="hljs-string">&quot;pixel-art-xl.safetensors&quot;</span>, adapter_name=<span class="hljs-string">&quot;pixel&quot;</span>)
pipeline.set_adapters([<span class="hljs-string">&quot;cinematic&quot;</span>, <span class="hljs-string">&quot;pixel&quot;</span>], adapter_weights=[<span class="hljs-number">0.5</span>, <span class="hljs-number">0.5</span>])`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Wr);var Br=e(Wr,2),qs=r(Br);a(qs,{name:"set_lora_device",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L933",parameters:[{name:"adapter_names",val:": list[str]"},{name:"device",val:": torch.device | str | int"}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device.adapter_names",description:`<strong>adapter_names</strong> (<code>list[str]</code>) &#x2014;
list of adapters to send device to.`,name:"adapter_names"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device.device",description:`<strong>device</strong> (<code>torch.device | str | int</code>) &#x2014;
Device to send the adapters to. Can be either a torch device, a str or an integer.`,name:"device"}]});var vl=e(qs,6);p(vl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device.example",children:(t,n)=>{c(t,{code:"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",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.load_lora_weights(path_1, adapter_name=<span class="hljs-string">&quot;adapter-1&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.load_lora_weights(path_2, adapter_name=<span class="hljs-string">&quot;adapter-2&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.set_adapters(<span class="hljs-string">&quot;adapter-1&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>image_1 = pipe(**kwargs)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># switch to adapter-2, offload adapter-1</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">&quot;adapter-1&quot;</span>], device=<span class="hljs-string">&quot;cpu&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">&quot;adapter-2&quot;</span>], device=<span class="hljs-string">&quot;cuda:0&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.set_adapters(<span class="hljs-string">&quot;adapter-2&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>image_2 = pipe(**kwargs)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># switch back to adapter-1, offload adapter-2</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">&quot;adapter-2&quot;</span>], device=<span class="hljs-string">&quot;cpu&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">&quot;adapter-1&quot;</span>], device=<span class="hljs-string">&quot;cuda:0&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>pipe.set_adapters(<span class="hljs-string">&quot;adapter-1&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>...`,lang:"python",wrap:!1})},$$slots:{default:!0}}),o(Br);var Vr=e(Br,2),bl=r(Vr);a(bl,{name:"unfuse_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L623",parameters:[{name:"components",val:": list[str] | None = None"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora.components",description:"<strong>components</strong> (<code>list[str]</code>) &#x2014; list of LoRA-injectable components to unfuse LoRA from.",name:"components"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora.unfuse_unet",description:"<strong>unfuse_unet</strong> (<code>bool</code>, defaults to <code>True</code>) &#x2014; Whether to unfuse the UNet LoRA parameters.",name:"unfuse_unet"},{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora.unfuse_text_encoder",description:`<strong>unfuse_text_encoder</strong> (<code>bool</code>, defaults to <code>True</code>) &#x2014;
Whether to unfuse the text encoder LoRA parameters. If the text encoder wasn&#x2019;t monkey-patched with the
LoRA parameters then it won&#x2019;t have any effect.`,name:"unfuse_text_encoder"}]}),s(2),o(Vr);var Ar=e(Vr,2),Ys=r(Ar);a(Ys,{name:"unload_lora_weights",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unload_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L513",parameters:[]});var Ll=e(Ys,4);p(Ll,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unload_lora_weights.example",children:(t,n)=>{var i=Cr(),l=e(_(i),2);c(l,{code:"JTIzJTIwQXNzdW1pbmclMjAlNjBwaXBlbGluZSU2MCUyMGlzJTIwYWxyZWFkeSUyMGxvYWRlZCUyMHdpdGglMjB0aGUlMjBMb1JBJTIwcGFyYW1ldGVycy4lMEFwaXBlbGluZS51bmxvYWRfbG9yYV93ZWlnaHRzKCklMEEuLi4=",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment"># Assuming `pipeline` is already loaded with the LoRA parameters.</span>\n<span class="hljs-meta">&gt;&gt;&gt; </span>pipeline.unload_lora_weights()\n<span class="hljs-meta">&gt;&gt;&gt; </span>...',lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Ar);var zs=e(Ar,2),xl=r(zs);a(xl,{name:"write_lora_layers",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.write_lora_layers",source:"https://github.com/huggingface/diffusers/blob/vr_14358/src/diffusers/loaders/lora_base.py#L1010",parameters:[{name:"state_dict",val:": dict[str, torch.Tensor]"},{name:"save_directory",val:": str"},{name:"is_main_process",val:": bool"},{name:"weight_name",val:": str"},{name:"save_function",val:": Callable"},{name:"safe_serialization",val:": bool"},{name:"lora_adapter_metadata",val:": dict | None = None"}]}),s(2),o(zs),o(Jr);var yl=e(Jr,2);Tl(yl,{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/en/api/loaders/lora.md"}),s(2),f(Qs,qr),Ul()}export{Gl as component};