Buckets:
| import"../chunks/DsnmJJEf.js";import{i as Bl,h as Vl,C as Al,H as d,D as a,E as Cl,s as ql,a as c}from"../chunks/BtE7mKSK.js";import{p as Yl,o as zl,s as e,f as _,a as f,b as Hl,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 Ql='{"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":"MiniMaxH3LoraLoaderMixin","local":"diffusers.loaders.MiniMaxH3LoraLoaderMixin","sections":[],"depth":2},{"title":"LoraBaseMixin","local":"diffusers.loaders.lora_base.LoraBaseMixin","sections":[],"depth":2}],"depth":1}';var Pl=u('<meta name="hf:doc:metadata"/>'),m=u("<p>Example:</p> <!>",1),Er=u("<p>Examples:</p> <!>",1),El=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_14386/en/api/models/unet2d-cond#diffusers.UNet2DConditionModel">UNet2DConditionModel</a>, for example) or a Transformer (<a href="/docs/diffusers/pr_14386/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>MiniMaxH3LoraLoaderMixin</code> provides similar functions for <a href="https://huggingface.co/docs/diffusers/main/en/api/pipelines/minimax_h3" rel="nofollow">MiniMax-H3</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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/flux2_transformer#diffusers.Flux2Transformer2DModel">Flux2Transformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/ltx2_video_transformer3d#diffusers.LTX2VideoTransformer3DModel">LTX2VideoTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/cogvideox_transformer3d#diffusers.CogVideoXTransformer3DModel">CogVideoXTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/mochi_transformer3d#diffusers.MochiTransformer3DModel">MochiTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/aura_flow_transformer2d#diffusers.AuraFlowTransformer2DModel">AuraFlowTransformer2DModel</a> Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/ltx_video_transformer3d#diffusers.LTXVideoTransformer3DModel">LTXVideoTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/sana_transformer2d#diffusers.SanaTransformer2DModel">SanaTransformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/helios_transformer3d#diffusers.HeliosTransformer3DModel">HeliosTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/en/api/pipelines/helios#diffusers.HeliosPipeline">HeliosPipeline</a> and <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/hunyuan_video_transformer_3d#diffusers.HunyuanVideoTransformer3DModel">HunyuanVideoTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/wan_transformer_3d#diffusers.WanTransformer3DModel">WanTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/wan_transformer_3d#diffusers.WanTransformer3DModel">WanTransformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/cosmos_transformer3d#diffusers.CosmosTransformer3DModel">CosmosTransformer3DModel</a> and <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/en/api/models/ace_step_transformer#diffusers.AceStepTransformer1DModel">AceStepTransformer1DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/hidream_image_transformer#diffusers.HiDreamImageTransformer2DModel">HiDreamImageTransformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/qwenimage_transformer2d#diffusers.QwenImageTransformer2DModel">QwenImageTransformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/z_image_transformer2d#diffusers.ZImageTransformer2DModel">ZImageTransformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/cosmos_transformer3d#diffusers.CosmosTransformer3DModel">CosmosTransformer3DModel</a>, Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/ideogram4_transformer2d#diffusers.Ideogram4Transformer2DModel">Ideogram4Transformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/krea2_transformer2d#diffusers.Krea2Transformer2DModel">Krea2Transformer2DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/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_14386/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_14386/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_14386/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_14386/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_14386/en/api/models/minimax_h3_transformer3d#diffusers.MiniMaxH3Transformer3DModel">MiniMaxH3Transformer3DModel</a>. Specific to <a href="/docs/diffusers/pr_14386/en/api/pipelines/minimax_h3#diffusers.MiniMaxH3ModularPipeline">MiniMaxH3ModularPipeline</a>.</p> <p>MiniMax-H3 ships two independent DiT partitions with identical module names (a LoRA for one loads into the other | |
| and degrades output), so routing is explicit: converted state dicts target <code>transformer.</code>; reach <code>transformer_ref</code> with a <code>transformer_ref.</code>-prefixed file or <code>load_into_transformer_ref=True</code>.</p> <p>LoRAs trained against a pruned checkpoint (the <code>*_pruned_*</code> files in <a href="https://huggingface.co/Comfy-Org/MiniMax-H3" rel="nofollow">Comfy-Org/MiniMax-H3</a>; <a href="https://huggingface.co/joyfox/MiniMax-H3-Turbo" rel="nofollow">joyfox/MiniMax-H3-Turbo</a> is one) fail with a size mismatch. | |
| Alpha-less files load at <code>alpha == rank</code> (scale 1.0, the convention stated by e.g. <a href="https://huggingface.co/larryvrh/MiniMax-H3-Turbo-Lora" rel="nofollow">larryvrh/MiniMax-H3-Turbo-Lora</a>); a <code>__metadata__</code> <code>alpha</code> entry (e.g. <a href="https://huggingface.co/lightx2v/Minimax-h3-Turbo" rel="nofollow">lightx2v/Minimax-h3-Turbo</a>’s 8-step file), when | |
| present, is honored instead.</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_14386/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>Load LoRA layers into the <code>transformer_ref</code> partition. <code>prefix</code> is the component name the keys carry, which is <code>transformer_ref</code> for a file that names the partition and <code>transformer</code> for one routed here by <code>load_into_transformer_ref=True</code>. See <a href="/docs/diffusers/pr_14386/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>Load LoRA layers into <code>transformer</code> or, with <code>load_into_transformer_ref=True</code>, into <code>transformer_ref</code>. See <a href="/docs/diffusers/pr_14386/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_14386/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 layers of one or both MiniMax-H3 partitions. Which partition a LoRA belongs to is not recoverable | |
| from its keys, so this is the only way to publish an H3 LoRA that records it. See <a href="/docs/diffusers/pr_14386/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 an(oi,si){Yl(si,!1),zl(()=>{new URLSearchParams(window.location.search).get("fw")}),Bl();var Kr=El();Vl("yjofn9",t=>{var n=Pl();ql(n,"content",Ql),f(t,n)});var $r=e(_(Kr),2);Al($r,{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"});var Or=e($r,2);d(Or,{title:"LoRA",local:"lora",headingTag:"h1"});var eo=e(Or,8);d(eo,{title:"LoraBaseMixin",local:"diffusers.loaders.lora_base.LoraBaseMixin",headingTag:"h2"});var h=e(eo,2),ao=r(h);a(ao,{name:"class diffusers.loaders.lora_base.LoraBaseMixin",anchor:"diffusers.loaders.lora_base.LoraBaseMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L486",parameters:[]});var g=e(ao,4),ro=r(g);a(ro,{name:"delete_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L856",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>) — | |
| The names of the adapters to delete.`,name:"adapter_names"}]});var ii=e(ro,4);p(ii,{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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"jbilcke-hf/sdxl-cinematic-1"</span>, weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, adapter_names=<span class="hljs-string">"cinematic"</span> | |
| ) | |
| pipeline.delete_adapters(<span class="hljs-string">"cinematic"</span>)`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(g);var v=e(g,2),oo=r(v);a(oo,{name:"disable_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.disable_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L796",parameters:[]});var ti=e(oo,4);p(ti,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.disable_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image | |
| <span class="hljs-keyword">import</span> torch | |
| pipeline = AutoPipelineForText2Image.from_pretrained( | |
| <span class="hljs-string">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"jbilcke-hf/sdxl-cinematic-1"</span>, weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, adapter_name=<span class="hljs-string">"cinematic"</span> | |
| ) | |
| pipeline.disable_lora()`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(v);var b=e(v,2),so=r(b);a(so,{name:"enable_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L826",parameters:[]});var di=e(so,4);p(di,{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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"jbilcke-hf/sdxl-cinematic-1"</span>, weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, adapter_name=<span class="hljs-string">"cinematic"</span> | |
| ) | |
| pipeline.enable_lora()`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(b);var L=e(b,2),li=r(L);a(li,{name:"enable_lora_hotswap",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L1003",parameters:[{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap.target_rank",description:`<strong>target_rank</strong> (<code>int</code>) — | |
| 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>"error"</code>) — | |
| How to handle a model that is already compiled. The check can return the following messages: | |
| <ul> | |
| <li>“error” (default): raise an error</li> | |
| <li>“warn”: issue a warning</li> | |
| <li>“ignore”: do nothing</li> | |
| </ul>`,name:"check_compiled"}]}),s(2),o(L);var x=e(L,2),io=r(x);a(io,{name:"fuse_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L544",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> — (<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) — | |
| 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>) — | |
| 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>) — | |
| Adapter names to be used for fusing. If nothing is passed, all active adapters will be fused.`,name:"adapter_names"}]});var ni=e(io,4);p(ni,{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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights(<span class="hljs-string">"nerijs/pixel-art-xl"</span>, weight_name=<span class="hljs-string">"pixel-art-xl.safetensors"</span>, adapter_name=<span class="hljs-string">"pixel"</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),to=r(y);a(to,{name:"get_active_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_active_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L894",parameters:[]});var ci=e(to,4);p(ci,{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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights(<span class="hljs-string">"CiroN2022/toy-face"</span>, weight_name=<span class="hljs-string">"toy_face_sdxl.safetensors"</span>, adapter_name=<span class="hljs-string">"toy"</span>) | |
| pipeline.get_active_adapters()`,lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(y);var M=e(y,2),fi=r(M);a(fi,{name:"get_list_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_list_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L927",parameters:[]}),s(2),o(M);var w=e(M,2),lo=r(w);a(lo,{name:"set_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L693",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>) — | |
| 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>) — | |
| 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 pi=e(lo,4);p(pi,{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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"jbilcke-hf/sdxl-cinematic-1"</span>, weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, adapter_name=<span class="hljs-string">"cinematic"</span> | |
| ) | |
| pipeline.load_lora_weights(<span class="hljs-string">"nerijs/pixel-art-xl"</span>, weight_name=<span class="hljs-string">"pixel-art-xl.safetensors"</span>, adapter_name=<span class="hljs-string">"pixel"</span>) | |
| pipeline.set_adapters([<span class="hljs-string">"cinematic"</span>, <span class="hljs-string">"pixel"</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(w);var S=e(w,2),no=r(S);a(no,{name:"set_lora_device",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L949",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>) — | |
| 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>) — | |
| Device to send the adapters to. Can be either a torch device, a str or an integer.`,name:"device"}]});var _i=e(no,6);p(_i,{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">>>> </span>pipe.load_lora_weights(path_1, adapter_name=<span class="hljs-string">"adapter-1"</span>) | |
| <span class="hljs-meta">>>> </span>pipe.load_lora_weights(path_2, adapter_name=<span class="hljs-string">"adapter-2"</span>) | |
| <span class="hljs-meta">>>> </span>pipe.set_adapters(<span class="hljs-string">"adapter-1"</span>) | |
| <span class="hljs-meta">>>> </span>image_1 = pipe(**kwargs) | |
| <span class="hljs-meta">>>> </span><span class="hljs-comment"># switch to adapter-2, offload adapter-1</span> | |
| <span class="hljs-meta">>>> </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">"adapter-1"</span>], device=<span class="hljs-string">"cpu"</span>) | |
| <span class="hljs-meta">>>> </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">"adapter-2"</span>], device=<span class="hljs-string">"cuda:0"</span>) | |
| <span class="hljs-meta">>>> </span>pipe.set_adapters(<span class="hljs-string">"adapter-2"</span>) | |
| <span class="hljs-meta">>>> </span>image_2 = pipe(**kwargs) | |
| <span class="hljs-meta">>>> </span><span class="hljs-comment"># switch back to adapter-1, offload adapter-2</span> | |
| <span class="hljs-meta">>>> </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">"adapter-2"</span>], device=<span class="hljs-string">"cpu"</span>) | |
| <span class="hljs-meta">>>> </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">"adapter-1"</span>], device=<span class="hljs-string">"cuda:0"</span>) | |
| <span class="hljs-meta">>>> </span>pipe.set_adapters(<span class="hljs-string">"adapter-1"</span>) | |
| <span class="hljs-meta">>>> </span>...`,lang:"python",wrap:!1})},$$slots:{default:!0}}),o(S);var T=e(S,2),mi=r(T);a(mi,{name:"unfuse_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L631",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>) — 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>) — 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>) — | |
| Whether to unfuse the text encoder LoRA parameters. If the text encoder wasn’t monkey-patched with the | |
| LoRA parameters then it won’t have any effect.`,name:"unfuse_text_encoder"}]}),s(2),o(T);var N=e(T,2),co=r(N);a(co,{name:"unload_lora_weights",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unload_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L521",parameters:[]});var ui=e(co,4);p(ui,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unload_lora_weights.example",children:(t,n)=>{var i=Er(),l=e(_(i),2);c(l,{code:"JTIzJTIwQXNzdW1pbmclMjAlNjBwaXBlbGluZSU2MCUyMGlzJTIwYWxyZWFkeSUyMGxvYWRlZCUyMHdpdGglMjB0aGUlMjBMb1JBJTIwcGFyYW1ldGVycy4lMEFwaXBlbGluZS51bmxvYWRfbG9yYV93ZWlnaHRzKCklMEEuLi4=",highlighted:'<span class="hljs-meta">>>> </span><span class="hljs-comment"># Assuming `pipeline` is already loaded with the LoRA parameters.</span>\n<span class="hljs-meta">>>> </span>pipeline.unload_lora_weights()\n<span class="hljs-meta">>>> </span>...',lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(N);var fo=e(N,2),hi=r(fo);a(hi,{name:"write_lora_layers",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.write_lora_layers",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L1026",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(fo),o(h);var po=e(h,2);d(po,{title:"StableDiffusionLoraLoaderMixin",local:"diffusers.loaders.StableDiffusionLoraLoaderMixin",headingTag:"h2"});var k=e(po,2),_o=r(k);a(_o,{name:"class diffusers.loaders.StableDiffusionLoraLoaderMixin",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L133",parameters:[]});var R=e(_o,4),gi=r(R);a(gi,{name:"load_lora_into_text_encoder",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_text_encoder",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L403",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>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| See <a href="/docs/diffusers/pr_14386/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>) — | |
| Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won’t be derived | |
| from the state dict.`,name:"metadata"}]}),s(2),o(R);var U=e(R,2),vi=r(U);a(vi,{name:"load_lora_into_unet",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L349",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.StableDiffusionLoraLoaderMixin.load_lora_into_unet.state_dict",description:`<strong>state_dict</strong> (<code>dict</code>) — | |
| 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.StableDiffusionLoraLoaderMixin.load_lora_into_unet.network_alphas",description:`<strong>network_alphas</strong> (<code>dict[str, float]</code>) — | |
| 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_unet.unet",description:`<strong>unet</strong> (<code>UNet2DConditionModel</code>) — | |
| The UNet model to load the LoRA layers into.`,name:"unet"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet.adapter_name",description:`<strong>adapter_name</strong> (<code>str</code>, <em>optional</em>) — | |
| 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_unet.low_cpu_mem_usage",description:`<strong>low_cpu_mem_usage</strong> (<code>bool</code>, <em>optional</em>) — | |
| Speed up model loading only loading the pretrained LoRA weights and not initializing the random | |
| weights.`,name:"low_cpu_mem_usage"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet.hotswap",description:`<strong>hotswap</strong> (<code>bool</code>, <em>optional</em>) — | |
| See <a href="/docs/diffusers/pr_14386/en/api/loaders/lora#diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights">load_lora_weights()</a>.`,name:"hotswap"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_into_unet.metadata",description:`<strong>metadata</strong> (<code>dict</code>) — | |
| Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won’t be derived | |
| from the state dict.`,name:"metadata"}]}),s(2),o(U);var D=e(U,2),bi=r(D);a(bi,{name:"load_lora_weights",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L143",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:""}],parametersDescription:[{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.load_lora_weights.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>) — | |
| See <a href="/docs/diffusers/pr_14386/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>) — | |
| 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_weights.low_cpu_mem_usage",description:`<strong>low_cpu_mem_usage</strong> (<code>bool</code>, <em>optional</em>) — | |
| 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_weights.hotswap",description:`<strong>hotswap</strong> (<code>bool</code>, <em>optional</em>) — | |
| 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(D);var J=e(D,2),Li=r(J);a(Li,{name:"lora_state_dict",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L238",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>) — | |
| 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_14386/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>) — | |
| 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.StableDiffusionLoraLoaderMixin.lora_state_dict.force_download",description:`<strong>force_download</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>False</code>) — | |
| 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.StableDiffusionLoraLoaderMixin.lora_state_dict.proxies",description:`<strong>proxies</strong> (<code>dict[str, str]</code>, <em>optional</em>) — | |
| A dictionary of proxy servers to use by protocol or endpoint, for example, <code>{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}</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>) — | |
| Whether to only load local model weights and configuration files or not. If set to <code>True</code>, the model | |
| won’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>) — | |
| 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.StableDiffusionLoraLoaderMixin.lora_state_dict.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>, defaults to <code>"main"</code>) — | |
| 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>""</code>) — | |
| 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) — | |
| 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) — | |
| When enabled, additionally return the LoRA adapter metadata, typically found in the state dict.`,name:"return_lora_metadata"}]}),s(4),o(J);var mo=e(J,2),xi=r(mo);a(xi,{name:"save_lora_weights",anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L461",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>) — | |
| Directory to save LoRA parameters to. Will be created if it doesn’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>) — | |
| 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>) — | |
| 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 🤗 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>) — | |
| 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>) — | |
| 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>) — | |
| Whether to save the model using <code>safetensors</code> or the traditional PyTorch way with <code>pickle</code>.`,name:"safe_serialization"},{anchor:"diffusers.loaders.StableDiffusionLoraLoaderMixin.save_lora_weights.unet_lora_adapter_metadata",description:`<strong>unet_lora_adapter_metadata</strong> — | |
| 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> — | |
| LoRA adapter metadata associated with the text encoder to be serialized with the state dict.`,name:"text_encoder_lora_adapter_metadata"}]}),s(2),o(mo),o(k);var uo=e(k,2);d(uo,{title:"StableDiffusionXLLoraLoaderMixin",local:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin",headingTag:"h2"});var F=e(uo,2),ho=r(F);a(ho,{name:"class diffusers.loaders.StableDiffusionXLLoraLoaderMixin",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L580",parameters:[]});var Z=e(ho,4),yi=r(Z);a(yi,{name:"fuse_lora",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L933",parameters:[{name:"components",val:": list = ['unet', '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(Z);var X=e(Z,2),Mi=r(X);a(Mi,{name:"load_lora_into_text_encoder",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L826",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.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.state_dict",description:`<strong>state_dict</strong> (<code>dict</code>) — | |
| 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.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.network_alphas",description:`<strong>network_alphas</strong> (<code>dict[str, float]</code>) — | |
| 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.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.text_encoder",description:`<strong>text_encoder</strong> (<code>CLIPTextModel</code>) — | |
| The text encoder model to load the LoRA layers into.`,name:"text_encoder"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.prefix",description:`<strong>prefix</strong> (<code>str</code>) — | |
| Expected prefix of the <code>text_encoder</code> in the <code>state_dict</code>.`,name:"prefix"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.lora_scale",description:`<strong>lora_scale</strong> (<code>float</code>) — | |
| 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.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.adapter_name",description:`<strong>adapter_name</strong> (<code>str</code>, <em>optional</em>) — | |
| 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.StableDiffusionXLLoraLoaderMixin.load_lora_into_text_encoder.low_cpu_mem_usage",description:`<strong>low_cpu_mem_usage</strong> (<code>bool</code>, <em>optional</em>) — | |
| 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>) — | |
| See <a href="/docs/diffusers/pr_14386/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>) — | |
| Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won’t be derived | |
| from the state dict.`,name:"metadata"}]}),s(2),o(X);var j=e(X,2),wi=r(j);a(wi,{name:"load_lora_into_unet",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L771",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>) — | |
| 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>) — | |
| 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.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet.unet",description:`<strong>unet</strong> (<code>UNet2DConditionModel</code>) — | |
| The UNet model to load the LoRA layers into.`,name:"unet"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet.adapter_name",description:`<strong>adapter_name</strong> (<code>str</code>, <em>optional</em>) — | |
| 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.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet.low_cpu_mem_usage",description:`<strong>low_cpu_mem_usage</strong> (<code>bool</code>, <em>optional</em>) — | |
| Speed up model loading only loading the pretrained LoRA weights and not initializing the random | |
| weights.`,name:"low_cpu_mem_usage"},{anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_into_unet.hotswap",description:`<strong>hotswap</strong> (<code>bool</code>, <em>optional</em>) — | |
| See <a href="/docs/diffusers/pr_14386/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>) — | |
| Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won’t be derived | |
| from the state dict.`,name:"metadata"}]}),s(2),o(j);var I=e(j,2),Si=r(I);a(Si,{name:"load_lora_weights",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L591",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),Ti=r(G);a(Ti,{name:"lora_state_dict",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L659",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>) — | |
| 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_14386/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>) — | |
| 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>) — | |
| 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>) — | |
| A dictionary of proxy servers to use by protocol or endpoint, for example, <code>{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}</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>) — | |
| Whether to only load local model weights and configuration files or not. If set to <code>True</code>, the model | |
| won’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>) — | |
| 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>"main"</code>) — | |
| 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.StableDiffusionXLLoraLoaderMixin.lora_state_dict.subfolder",description:`<strong>subfolder</strong> (<code>str</code>, <em>optional</em>, defaults to <code>""</code>) — | |
| 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) — | |
| 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) — | |
| 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),Ni=r(W);a(Ni,{name:"save_lora_weights",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L885",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 go=e(W,2),ki=r(go);a(ki,{name:"unfuse_lora",anchor:"diffusers.loaders.StableDiffusionXLLoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L952",parameters:[{name:"components",val:": list = ['unet', 'text_encoder', 'text_encoder_2']"},{name:"**kwargs",val:""}]}),s(2),o(go),o(F);var vo=e(F,2);d(vo,{title:"SD3LoraLoaderMixin",local:"diffusers.loaders.SD3LoraLoaderMixin",headingTag:"h2"});var B=e(vo,2),bo=r(B);a(bo,{name:"class diffusers.loaders.SD3LoraLoaderMixin",anchor:"diffusers.loaders.SD3LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L959",parameters:[]});var V=e(bo,6),Ri=r(V);a(Ri,{name:"fuse_lora",anchor:"diffusers.loaders.SD3LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1220",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),Ui=r(A);a(Ui,{name:"load_lora_into_text_encoder",anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_text_encoder",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1111",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>) — | |
| 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.SD3LoraLoaderMixin.load_lora_into_text_encoder.network_alphas",description:`<strong>network_alphas</strong> (<code>dict[str, float]</code>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| 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.SD3LoraLoaderMixin.load_lora_into_text_encoder.hotswap",description:`<strong>hotswap</strong> (<code>bool</code>, <em>optional</em>) — | |
| See <a href="/docs/diffusers/pr_14386/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>) — | |
| Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won’t be derived | |
| from the state dict.`,name:"metadata"}]}),s(2),o(A);var C=e(A,2),Di=r(C);a(Di,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1085",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(C);var q=e(C,2),Ji=r(q);a(Ji,{name:"load_lora_weights",anchor:"diffusers.loaders.SD3LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1026",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"adapter_name",val:" = None"},{name:"hotswap",val:": bool = False"},{name:"**kwargs",val:""}]}),s(2),o(q);var Y=e(q,2),Fi=r(Y);a(Fi,{name:"lora_state_dict",anchor:"diffusers.loaders.SD3LoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L972",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(Y);var z=e(Y,2),Zi=r(z);a(Zi,{name:"save_lora_weights",anchor:"diffusers.loaders.SD3LoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1170",parameters:[{name:"save_directory",val:": str | os.PathLike"},{name:"transformer_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:"transformer_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(z);var Lo=e(z,2),Xi=r(Lo);a(Xi,{name:"unfuse_lora",anchor:"diffusers.loaders.SD3LoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1240",parameters:[{name:"components",val:": list = ['transformer', 'text_encoder', 'text_encoder_2']"},{name:"**kwargs",val:""}]}),s(2),o(Lo),o(B);var xo=e(B,2);d(xo,{title:"FluxLoraLoaderMixin",local:"diffusers.loaders.FluxLoraLoaderMixin",headingTag:"h2"});var H=e(xo,2),yo=r(H);a(yo,{name:"class diffusers.loaders.FluxLoraLoaderMixin",anchor:"diffusers.loaders.FluxLoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1436",parameters:[]});var Q=e(yo,6),ji=r(Q);a(ji,{name:"fuse_lora",anchor:"diffusers.loaders.FluxLoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1874",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(Q);var P=e(Q,2),Ii=r(P);a(Ii,{name:"load_lora_into_text_encoder",anchor:"diffusers.loaders.FluxLoraLoaderMixin.load_lora_into_text_encoder",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1751",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.FluxLoraLoaderMixin.load_lora_into_text_encoder.state_dict",description:`<strong>state_dict</strong> (<code>dict</code>) — | |
| 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.FluxLoraLoaderMixin.load_lora_into_text_encoder.network_alphas",description:`<strong>network_alphas</strong> (<code>dict[str, float]</code>) — | |
| 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>) — | |
| 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>) — | |
| 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>) — | |
| 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.FluxLoraLoaderMixin.load_lora_into_text_encoder.adapter_name",description:`<strong>adapter_name</strong> (<code>str</code>, <em>optional</em>) — | |
| 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.FluxLoraLoaderMixin.load_lora_into_text_encoder.low_cpu_mem_usage",description:`<strong>low_cpu_mem_usage</strong> (<code>bool</code>, <em>optional</em>) — | |
| 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.FluxLoraLoaderMixin.load_lora_into_text_encoder.hotswap",description:`<strong>hotswap</strong> (<code>bool</code>, <em>optional</em>) — | |
| See <a href="/docs/diffusers/pr_14386/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>) — | |
| Optional LoRA adapter metadata. When supplied, the <code>LoraConfig</code> arguments of <code>peft</code> won’t be derived | |
| from the state dict.`,name:"metadata"}]}),s(2),o(P);var E=e(P,2),Gi=r(E);a(Gi,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.FluxLoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1670",parameters:[{name:"state_dict",val:""},{name:"network_alphas",val:""},{name:"transformer",val:""},{name:"adapter_name",val:" = None"},{name:"metadata",val:" = None"},{name:"_pipeline",val:" = None"},{name:"low_cpu_mem_usage",val:" = False"},{name:"hotswap",val:": bool = False"}]}),s(2),o(E);var K=e(E,2),Wi=r(K);a(Wi,{name:"load_lora_weights",anchor:"diffusers.loaders.FluxLoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1574",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(K);var $=e(K,2),Bi=r($);a(Bi,{name:"lora_state_dict",anchor:"diffusers.loaders.FluxLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1449",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"return_alphas",val:": bool = False"},{name:"**kwargs",val:""}]}),s(2),o($);var O=e($,2),Vi=r(O);a(Vi,{name:"save_lora_weights",anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1810",parameters:[{name:"save_directory",val:": str | os.PathLike"},{name:"transformer_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:"transformer_lora_adapter_metadata",val:" = None"},{name:"text_encoder_lora_adapter_metadata",val:" = None"}],parametersDescription:[{anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights.save_directory",description:`<strong>save_directory</strong> (<code>str</code> or <code>os.PathLike</code>) — | |
| Directory to save LoRA parameters to. Will be created if it doesn’t exist.`,name:"save_directory"},{anchor:"diffusers.loaders.FluxLoraLoaderMixin.save_lora_weights.transformer_lora_layers",description:`<strong>transformer_lora_layers</strong> (<code>dict[str, torch.nn.Module]</code> or <code>dict[str, torch.Tensor]</code>) — | |
| 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>) — | |
| 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 🤗 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>) — | |
| 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>) — | |
| 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>) — | |
| 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> — | |
| 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> — | |
| 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),Ai=r(ee);a(Ai,{name:"unfuse_lora",anchor:"diffusers.loaders.FluxLoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1906",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>) — list of LoRA-injectable components to unfuse LoRA from.",name:"components"}]}),s(2),o(ee);var Mo=e(ee,2),wo=r(Mo);a(wo,{name:"unload_lora_weights",anchor:"diffusers.loaders.FluxLoraLoaderMixin.unload_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L1921",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>) — 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 Ci=e(wo,4);p(Ci,{anchor:"diffusers.loaders.FluxLoraLoaderMixin.unload_lora_weights.example",children:(t,n)=>{var i=Er(),l=e(_(i),2);c(l,{code:"JTIzJTIwQXNzdW1pbmclMjAlNjBwaXBlbGluZSU2MCUyMGlzJTIwYWxyZWFkeSUyMGxvYWRlZCUyMHdpdGglMjB0aGUlMjBMb1JBJTIwcGFyYW1ldGVycy4lMEFwaXBlbGluZS51bmxvYWRfbG9yYV93ZWlnaHRzKCklMEEuLi4=",highlighted:'<span class="hljs-meta">>>> </span><span class="hljs-comment"># Assuming `pipeline` is already loaded with the LoRA parameters.</span>\n<span class="hljs-meta">>>> </span>pipeline.unload_lora_weights()\n<span class="hljs-meta">>>> </span>...',lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Mo),o(H);var So=e(H,2);d(So,{title:"Flux2LoraLoaderMixin",local:"diffusers.loaders.Flux2LoraLoaderMixin",headingTag:"h2"});var ae=e(So,2),To=r(ae);a(To,{name:"class diffusers.loaders.Flux2LoraLoaderMixin",anchor:"diffusers.loaders.Flux2LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5763",parameters:[]});var re=e(To,4),qi=r(re);a(qi,{name:"fuse_lora",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5939",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(re);var oe=e(re,2),Yi=r(oe);a(Yi,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5876",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),zi=r(se);a(zi,{name:"load_lora_weights",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5840",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),Hi=r(ie);a(Hi,{name:"lora_state_dict",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5771",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),Qi=r(te);a(Qi,{name:"save_lora_weights",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5903",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 No=e(te,2),Pi=r(No);a(Pi,{name:"unfuse_lora",anchor:"diffusers.loaders.Flux2LoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5959",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(No),o(ae);var ko=e(ae,2);d(ko,{title:"ErnieImageLoraLoaderMixin",local:"diffusers.loaders.ErnieImageLoraLoaderMixin",headingTag:"h2"});var de=e(ko,2),Ro=r(de);a(Ro,{name:"class diffusers.loaders.ErnieImageLoraLoaderMixin",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6162",parameters:[]});var le=e(Ro,4),Ei=r(le);a(Ei,{name:"fuse_lora",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6335",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(le);var ne=e(le,2),Ki=r(ne);a(Ki,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6272",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 ce=e(ne,2),$i=r(ce);a($i,{name:"load_lora_weights",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6236",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),Oi=r(fe);a(Oi,{name:"lora_state_dict",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6170",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(fe);var pe=e(fe,2),et=r(pe);a(et,{name:"save_lora_weights",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6299",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(pe);var Uo=e(pe,2),at=r(Uo);a(at,{name:"unfuse_lora",anchor:"diffusers.loaders.ErnieImageLoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6355",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(Uo),o(de);var Do=e(de,2);d(Do,{title:"LTX2LoraLoaderMixin",local:"diffusers.loaders.LTX2LoraLoaderMixin",headingTag:"h2"});var _e=e(Do,2),Jo=r(_e);a(Jo,{name:"class diffusers.loaders.LTX2LoraLoaderMixin",anchor:"diffusers.loaders.LTX2LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2914",parameters:[]});var me=e(Jo,4),rt=r(me);a(rt,{name:"fuse_lora",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L3103",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),ot=r(ue);a(ot,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L3039",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),st=r(he);a(st,{name:"load_lora_weights",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2987",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(he);var ge=e(he,2),it=r(ge);a(it,{name:"lora_state_dict",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2923",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(ge);var ve=e(ge,2),tt=r(ve);a(tt,{name:"save_lora_weights",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L3067",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(ve);var Fo=e(ve,2),dt=r(Fo);a(dt,{name:"unfuse_lora",anchor:"diffusers.loaders.LTX2LoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L3123",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(Fo),o(_e);var Zo=e(_e,2);d(Zo,{title:"CogVideoXLoraLoaderMixin",local:"diffusers.loaders.CogVideoXLoraLoaderMixin",headingTag:"h2"});var be=e(Zo,2),Xo=r(be);a(Xo,{name:"class diffusers.loaders.CogVideoXLoraLoaderMixin",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2348",parameters:[]});var Le=e(Xo,4),lt=r(Le);a(lt,{name:"fuse_lora",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2507",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(Le);var xe=e(Le,2),nt=r(xe);a(nt,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2446",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(xe);var ye=e(xe,2),ct=r(ye);a(ct,{name:"load_lora_weights",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2411",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 Me=e(ye,2),ft=r(Me);a(ft,{name:"lora_state_dict",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2356",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(Me);var we=e(Me,2),pt=r(we);a(pt,{name:"save_lora_weights",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2473",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(we);var jo=e(we,2),_t=r(jo);a(_t,{name:"unfuse_lora",anchor:"diffusers.loaders.CogVideoXLoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2526",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(jo),o(be);var Io=e(be,2);d(Io,{title:"Mochi1LoraLoaderMixin",local:"diffusers.loaders.Mochi1LoraLoaderMixin",headingTag:"h2"});var Se=e(Io,2),Go=r(Se);a(Go,{name:"class diffusers.loaders.Mochi1LoraLoaderMixin",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2533",parameters:[]});var Te=e(Go,4),mt=r(Te);a(mt,{name:"fuse_lora",anchor:"diffusers.loaders.Mochi1LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L2695",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 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| State dict of the LoRA layers corresponding to the <code>text_encoder</code>. Must explicitly pass the text | |
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| 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 | |
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| 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 | |
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vr=e(gr,2),tl=r(vr);a(tl,{name:"save_lora_weights",anchor:"diffusers.loaders.KandinskyLoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L4020",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(vr);var js=e(vr,2),dl=r(js);a(dl,{name:"unfuse_lora",anchor:"diffusers.loaders.KandinskyLoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L4076",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(js),o(_r);var Is=e(_r,2);d(Is,{title:"Ideogram4LoraLoaderMixin",local:"diffusers.loaders.Ideogram4LoraLoaderMixin",headingTag:"h2"});var br=e(Is,2),Gs=r(br);a(Gs,{name:"class diffusers.loaders.Ideogram4LoraLoaderMixin",anchor:"diffusers.loaders.Ideogram4LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5966",parameters:[]});var Lr=e(Gs,4),ll=r(Lr);a(ll,{name:"fuse_lora",anchor:"diffusers.loaders.Ideogram4LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6135",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(Lr);var xr=e(Lr,2),nl=r(xr);a(nl,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.Ideogram4LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6072",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(xr);var yr=e(xr,2),cl=r(yr);a(cl,{name:"load_lora_weights",anchor:"diffusers.loaders.Ideogram4LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6036",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(yr);var Mr=e(yr,2),fl=r(Mr);a(fl,{name:"lora_state_dict",anchor:"diffusers.loaders.Ideogram4LoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5974",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(Mr);var wr=e(Mr,2),pl=r(wr);a(pl,{name:"save_lora_weights",anchor:"diffusers.loaders.Ideogram4LoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6099",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(wr);var Ws=e(wr,2),_l=r(Ws);a(_l,{name:"unfuse_lora",anchor:"diffusers.loaders.Ideogram4LoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6155",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(Ws),o(br);var Bs=e(br,2);d(Bs,{title:"Krea2LoraLoaderMixin",local:"diffusers.loaders.Krea2LoraLoaderMixin",headingTag:"h2"});var Sr=e(Bs,2),Vs=r(Sr);a(Vs,{name:"class diffusers.loaders.Krea2LoraLoaderMixin",anchor:"diffusers.loaders.Krea2LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5188",parameters:[]});var Tr=e(Vs,4),ml=r(Tr);a(ml,{name:"fuse_lora",anchor:"diffusers.loaders.Krea2LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5355",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(Tr);var Nr=e(Tr,2),ul=r(Nr);a(ul,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.Krea2LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5292",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(Nr);var kr=e(Nr,2),hl=r(kr);a(hl,{name:"load_lora_weights",anchor:"diffusers.loaders.Krea2LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5256",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(kr);var Rr=e(kr,2),gl=r(Rr);a(gl,{name:"lora_state_dict",anchor:"diffusers.loaders.Krea2LoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5196",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(Rr);var Ur=e(Rr,2),vl=r(Ur);a(vl,{name:"save_lora_weights",anchor:"diffusers.loaders.Krea2LoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5319",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(Ur);var As=e(Ur,2),bl=r(As);a(bl,{name:"unfuse_lora",anchor:"diffusers.loaders.Krea2LoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L5375",parameters:[{name:"components",val:": list = ['transformer']"},{name:"**kwargs",val:""}]}),s(2),o(As),o(Sr);var Cs=e(Sr,2);d(Cs,{title:"MiniMaxH3LoraLoaderMixin",local:"diffusers.loaders.MiniMaxH3LoraLoaderMixin",headingTag:"h2"});var Dr=e(Cs,2),qs=r(Dr);a(qs,{name:"class diffusers.loaders.MiniMaxH3LoraLoaderMixin",anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6743",parameters:[]});var Jr=e(qs,8),Ll=r(Jr);a(Ll,{name:"fuse_lora",anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L7092",parameters:[{name:"components",val:": list = ['transformer', 'transformer_ref']"},{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(Jr);var Fr=e(Jr,2),xl=r(Fr);a(xl,{name:"load_lora_into_transformer",anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin.load_lora_into_transformer",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6992",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(Fr);var Zr=e(Fr,2),yl=r(Zr);a(yl,{name:"load_lora_into_transformer_ref",anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin.load_lora_into_transformer_ref",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L7019",parameters:[{name:"state_dict",val:""},{name:"transformer_ref",val:""},{name:"prefix",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(Zr);var Xr=e(Zr,2),Ml=r(Xr);a(Ml,{name:"load_lora_weights",anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin.load_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6877",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:"load_into_transformer_ref",val:": bool = False"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin.load_lora_weights.load_into_transformer_ref",description:`<strong>load_into_transformer_ref</strong> (<code>bool</code>, defaults to <code>False</code>) — | |
| Load the <code>transformer.</code>-prefixed layers into the <code>transformer_ref</code> partition — the one the <code>ref2va</code> | |
| workflow denoises with — instead of <code>transformer</code>. Only needed when both partitions are loaded: a | |
| pipeline that holds <code>transformer_ref</code> alone routes there on its own.`,name:"load_into_transformer_ref"}]}),s(2),o(Xr);var jr=e(Xr,2),wl=r(jr);a(wl,{name:"lora_state_dict",anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin.lora_state_dict",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L6764",parameters:[{name:"pretrained_model_name_or_path_or_dict",val:": str | dict[str, torch.Tensor]"},{name:"**kwargs",val:""}]}),s(2),o(jr);var Ir=e(jr,2),Sl=r(Ir);a(Sl,{name:"save_lora_weights",anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin.save_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L7049",parameters:[{name:"save_directory",val:": str | os.PathLike"},{name:"transformer_lora_layers",val:": dict = None"},{name:"transformer_ref_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"},{name:"transformer_ref_lora_adapter_metadata",val:": dict | None = None"}]}),s(2),o(Ir);var Ys=e(Ir,2),Tl=r(Ys);a(Tl,{name:"unfuse_lora",anchor:"diffusers.loaders.MiniMaxH3LoraLoaderMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_pipeline.py#L7111",parameters:[{name:"components",val:": list = ['transformer', 'transformer_ref']"},{name:"**kwargs",val:""}]}),s(2),o(Ys),o(Dr);var zs=e(Dr,2);d(zs,{title:"LoraBaseMixin",local:"diffusers.loaders.lora_base.LoraBaseMixin",headingTag:"h2"});var Gr=e(zs,2),Hs=r(Gr);a(Hs,{name:"class diffusers.loaders.lora_base.LoraBaseMixin",anchor:"diffusers.loaders.lora_base.LoraBaseMixin",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L486",parameters:[]});var Wr=e(Hs,4),Qs=r(Wr);a(Qs,{name:"delete_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L856",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>) — | |
| The names of the adapters to delete.`,name:"adapter_names"}]});var Nl=e(Qs,4);p(Nl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.delete_adapters.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMEF1dG9QaXBlbGluZUZvclRleHQySW1hZ2UlMEFpbXBvcnQlMjB0b3JjaCUwQSUwQXBpcGVsaW5lJTIwJTNEJTIwQXV0b1BpcGVsaW5lRm9yVGV4dDJJbWFnZS5mcm9tX3ByZXRyYWluZWQoJTBBJTIwJTIwJTIwJTIwJTIyc3RhYmlsaXR5YWklMkZzdGFibGUtZGlmZnVzaW9uLXhsLWJhc2UtMS4wJTIyJTJDJTIwdG9yY2hfZHR5cGUlM0R0b3JjaC5mbG9hdDE2JTBBKS50byglMjJjdWRhJTIyKSUwQXBpcGVsaW5lLmxvYWRfbG9yYV93ZWlnaHRzKCUwQSUyMCUyMCUyMCUyMCUyMmpiaWxja2UtaGYlMkZzZHhsLWNpbmVtYXRpYy0xJTIyJTJDJTIwd2VpZ2h0X25hbWUlM0QlMjJweXRvcmNoX2xvcmFfd2VpZ2h0cy5zYWZldGVuc29ycyUyMiUyQyUyMGFkYXB0ZXJfbmFtZXMlM0QlMjJjaW5lbWF0aWMlMjIlMEEpJTBBcGlwZWxpbmUuZGVsZXRlX2FkYXB0ZXJzKCUyMmNpbmVtYXRpYyUyMik=",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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"jbilcke-hf/sdxl-cinematic-1"</span>, weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, adapter_names=<span class="hljs-string">"cinematic"</span> | |
| ) | |
| pipeline.delete_adapters(<span class="hljs-string">"cinematic"</span>)`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Wr);var Br=e(Wr,2),Ps=r(Br);a(Ps,{name:"disable_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.disable_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L796",parameters:[]});var kl=e(Ps,4);p(kl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.disable_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMEF1dG9QaXBlbGluZUZvclRleHQySW1hZ2UlMEFpbXBvcnQlMjB0b3JjaCUwQSUwQXBpcGVsaW5lJTIwJTNEJTIwQXV0b1BpcGVsaW5lRm9yVGV4dDJJbWFnZS5mcm9tX3ByZXRyYWluZWQoJTBBJTIwJTIwJTIwJTIwJTIyc3RhYmlsaXR5YWklMkZzdGFibGUtZGlmZnVzaW9uLXhsLWJhc2UtMS4wJTIyJTJDJTIwdG9yY2hfZHR5cGUlM0R0b3JjaC5mbG9hdDE2JTBBKS50byglMjJjdWRhJTIyKSUwQXBpcGVsaW5lLmxvYWRfbG9yYV93ZWlnaHRzKCUwQSUyMCUyMCUyMCUyMCUyMmpiaWxja2UtaGYlMkZzZHhsLWNpbmVtYXRpYy0xJTIyJTJDJTIwd2VpZ2h0X25hbWUlM0QlMjJweXRvcmNoX2xvcmFfd2VpZ2h0cy5zYWZldGVuc29ycyUyMiUyQyUyMGFkYXB0ZXJfbmFtZSUzRCUyMmNpbmVtYXRpYyUyMiUwQSklMEFwaXBlbGluZS5kaXNhYmxlX2xvcmEoKQ==",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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"jbilcke-hf/sdxl-cinematic-1"</span>, weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, adapter_name=<span class="hljs-string">"cinematic"</span> | |
| ) | |
| pipeline.disable_lora()`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Br);var Vr=e(Br,2),Es=r(Vr);a(Es,{name:"enable_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L826",parameters:[]});var Rl=e(Es,4);p(Rl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"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",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> AutoPipelineForText2Image | |
| <span class="hljs-keyword">import</span> torch | |
| pipeline = AutoPipelineForText2Image.from_pretrained( | |
| <span class="hljs-string">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"jbilcke-hf/sdxl-cinematic-1"</span>, weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, adapter_name=<span class="hljs-string">"cinematic"</span> | |
| ) | |
| pipeline.enable_lora()`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Vr);var Ar=e(Vr,2),Ul=r(Ar);a(Ul,{name:"enable_lora_hotswap",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L1003",parameters:[{name:"**kwargs",val:""}],parametersDescription:[{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.enable_lora_hotswap.target_rank",description:`<strong>target_rank</strong> (<code>int</code>) — | |
| 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>"error"</code>) — | |
| How to handle a model that is already compiled. The check can return the following messages: | |
| <ul> | |
| <li>“error” (default): raise an error</li> | |
| <li>“warn”: issue a warning</li> | |
| <li>“ignore”: do nothing</li> | |
| </ul>`,name:"check_compiled"}]}),s(2),o(Ar);var Cr=e(Ar,2),Ks=r(Cr);a(Ks,{name:"fuse_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.fuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L544",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> — (<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) — | |
| 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>) — | |
| 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>) — | |
| Adapter names to be used for fusing. If nothing is passed, all active adapters will be fused.`,name:"adapter_names"}]});var Dl=e(Ks,4);p(Dl,{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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights(<span class="hljs-string">"nerijs/pixel-art-xl"</span>, weight_name=<span class="hljs-string">"pixel-art-xl.safetensors"</span>, adapter_name=<span class="hljs-string">"pixel"</span>) | |
| pipeline.fuse_lora(lora_scale=<span class="hljs-number">0.7</span>)`,lang:"py",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Cr);var qr=e(Cr,2),$s=r(qr);a($s,{name:"get_active_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_active_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L894",parameters:[]});var Jl=e($s,4);p(Jl,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_active_adapters.example",children:(t,n)=>{var i=m(),l=e(_(i),2);c(l,{code:"ZnJvbSUyMGRpZmZ1c2VycyUyMGltcG9ydCUyMERpZmZ1c2lvblBpcGVsaW5lJTBBJTBBcGlwZWxpbmUlMjAlM0QlMjBEaWZmdXNpb25QaXBlbGluZS5mcm9tX3ByZXRyYWluZWQoJTBBJTIwJTIwJTIwJTIwJTIyc3RhYmlsaXR5YWklMkZzdGFibGUtZGlmZnVzaW9uLXhsLWJhc2UtMS4wJTIyJTJDJTBBKS50byglMjJjdWRhJTIyKSUwQXBpcGVsaW5lLmxvYWRfbG9yYV93ZWlnaHRzKCUyMkNpcm9OMjAyMiUyRnRveS1mYWNlJTIyJTJDJTIwd2VpZ2h0X25hbWUlM0QlMjJ0b3lfZmFjZV9zZHhsLnNhZmV0ZW5zb3JzJTIyJTJDJTIwYWRhcHRlcl9uYW1lJTNEJTIydG95JTIyKSUwQXBpcGVsaW5lLmdldF9hY3RpdmVfYWRhcHRlcnMoKQ==",highlighted:`<span class="hljs-keyword">from</span> diffusers <span class="hljs-keyword">import</span> DiffusionPipeline | |
| pipeline = DiffusionPipeline.from_pretrained( | |
| <span class="hljs-string">"stabilityai/stable-diffusion-xl-base-1.0"</span>, | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights(<span class="hljs-string">"CiroN2022/toy-face"</span>, weight_name=<span class="hljs-string">"toy_face_sdxl.safetensors"</span>, adapter_name=<span class="hljs-string">"toy"</span>) | |
| pipeline.get_active_adapters()`,lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(qr);var Yr=e(qr,2),Fl=r(Yr);a(Fl,{name:"get_list_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.get_list_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L927",parameters:[]}),s(2),o(Yr);var zr=e(Yr,2),Os=r(zr);a(Os,{name:"set_adapters",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_adapters",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L693",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>) — | |
| 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>) — | |
| 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 Zl=e(Os,4);p(Zl,{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">"stabilityai/stable-diffusion-xl-base-1.0"</span>, torch_dtype=torch.float16 | |
| ).to(<span class="hljs-string">"cuda"</span>) | |
| pipeline.load_lora_weights( | |
| <span class="hljs-string">"jbilcke-hf/sdxl-cinematic-1"</span>, weight_name=<span class="hljs-string">"pytorch_lora_weights.safetensors"</span>, adapter_name=<span class="hljs-string">"cinematic"</span> | |
| ) | |
| pipeline.load_lora_weights(<span class="hljs-string">"nerijs/pixel-art-xl"</span>, weight_name=<span class="hljs-string">"pixel-art-xl.safetensors"</span>, adapter_name=<span class="hljs-string">"pixel"</span>) | |
| pipeline.set_adapters([<span class="hljs-string">"cinematic"</span>, <span class="hljs-string">"pixel"</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(zr);var Hr=e(zr,2),ei=r(Hr);a(ei,{name:"set_lora_device",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.set_lora_device",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L949",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>) — | |
| 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>) — | |
| Device to send the adapters to. Can be either a torch device, a str or an integer.`,name:"device"}]});var Xl=e(ei,6);p(Xl,{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">>>> </span>pipe.load_lora_weights(path_1, adapter_name=<span class="hljs-string">"adapter-1"</span>) | |
| <span class="hljs-meta">>>> </span>pipe.load_lora_weights(path_2, adapter_name=<span class="hljs-string">"adapter-2"</span>) | |
| <span class="hljs-meta">>>> </span>pipe.set_adapters(<span class="hljs-string">"adapter-1"</span>) | |
| <span class="hljs-meta">>>> </span>image_1 = pipe(**kwargs) | |
| <span class="hljs-meta">>>> </span><span class="hljs-comment"># switch to adapter-2, offload adapter-1</span> | |
| <span class="hljs-meta">>>> </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">"adapter-1"</span>], device=<span class="hljs-string">"cpu"</span>) | |
| <span class="hljs-meta">>>> </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">"adapter-2"</span>], device=<span class="hljs-string">"cuda:0"</span>) | |
| <span class="hljs-meta">>>> </span>pipe.set_adapters(<span class="hljs-string">"adapter-2"</span>) | |
| <span class="hljs-meta">>>> </span>image_2 = pipe(**kwargs) | |
| <span class="hljs-meta">>>> </span><span class="hljs-comment"># switch back to adapter-1, offload adapter-2</span> | |
| <span class="hljs-meta">>>> </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">"adapter-2"</span>], device=<span class="hljs-string">"cpu"</span>) | |
| <span class="hljs-meta">>>> </span>pipeline.set_lora_device(adapter_names=[<span class="hljs-string">"adapter-1"</span>], device=<span class="hljs-string">"cuda:0"</span>) | |
| <span class="hljs-meta">>>> </span>pipe.set_adapters(<span class="hljs-string">"adapter-1"</span>) | |
| <span class="hljs-meta">>>> </span>...`,lang:"python",wrap:!1})},$$slots:{default:!0}}),o(Hr);var Qr=e(Hr,2),jl=r(Qr);a(jl,{name:"unfuse_lora",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unfuse_lora",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L631",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>) — 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>) — 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>) — | |
| Whether to unfuse the text encoder LoRA parameters. If the text encoder wasn’t monkey-patched with the | |
| LoRA parameters then it won’t have any effect.`,name:"unfuse_text_encoder"}]}),s(2),o(Qr);var Pr=e(Qr,2),ai=r(Pr);a(ai,{name:"unload_lora_weights",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unload_lora_weights",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L521",parameters:[]});var Il=e(ai,4);p(Il,{anchor:"diffusers.loaders.lora_base.LoraBaseMixin.unload_lora_weights.example",children:(t,n)=>{var i=Er(),l=e(_(i),2);c(l,{code:"JTIzJTIwQXNzdW1pbmclMjAlNjBwaXBlbGluZSU2MCUyMGlzJTIwYWxyZWFkeSUyMGxvYWRlZCUyMHdpdGglMjB0aGUlMjBMb1JBJTIwcGFyYW1ldGVycy4lMEFwaXBlbGluZS51bmxvYWRfbG9yYV93ZWlnaHRzKCklMEEuLi4=",highlighted:'<span class="hljs-meta">>>> </span><span class="hljs-comment"># Assuming `pipeline` is already loaded with the LoRA parameters.</span>\n<span class="hljs-meta">>>> </span>pipeline.unload_lora_weights()\n<span class="hljs-meta">>>> </span>...',lang:"python",wrap:!1}),f(t,i)},$$slots:{default:!0}}),o(Pr);var ri=e(Pr,2),Gl=r(ri);a(Gl,{name:"write_lora_layers",anchor:"diffusers.loaders.lora_base.LoraBaseMixin.write_lora_layers",source:"https://github.com/huggingface/diffusers/blob/vr_14386/src/diffusers/loaders/lora_base.py#L1026",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(ri),o(Gr);var Wl=e(Gr,2);Cl(Wl,{source:"https://github.com/huggingface/diffusers/blob/main/docs/source/en/api/loaders/lora.md"}),s(2),f(oi,Kr),Hl()}export{an as component}; | |
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