8000 [Feat] Support SDXL Kohya-style LoRA (#4287) · orpatashnik/diffusers@afb437b · GitHub
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[Feat] Support SDXL Kohya-style LoRA (huggingface#4287)
* sdxl lora changes. * better na 8000 me replacement. * better replacement. * debugging * debugging * debugging * debugging * debugging * remove print. * print state dict keys. * print * distingisuih better * debuggable. * fxi: tyests * fix: arg from training script. * access from class. * run style * debug * save intermediate * some simplifications for SDXL LoRA * styling * unet config is not needed in diffusers format. * fix: dynamic SGM block mapping for SDXL kohya loras (huggingface#4322) * Use lora compatible layers for linear proj_in/proj_out (huggingface#4323) * improve condition for using the sgm_diffusers mapping * informative comment. * load compatible keys and embedding layer maaping. * Get SDXL 1.0 example lora to load * simplify * specif ranks and hidden sizes. * better handling of k rank and hidden * debug * debug * debug * debug * debug * fix: alpha keys * add check for handling LoRAAttnAddedKVProcessor * sanity comment * modifications for text encoder SDXL * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * denugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * debugging * up * up * up * up * up * up * unneeded comments. * unneeded comments. * kwargs for the other attention processors. * kwargs for the other attention processors. * debugging * debugging * debugging * debugging * improve * debugging * debugging * more print * Fix alphas * debugging * debugging * debugging * debugging * debugging * debugging * clean up * clean up. * debugging * fix: text --------- Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Batuhan Taskaya <batuhan@python.org>
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‎docs/source/en/training/lora.md

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@@ -354,4 +354,52 @@ directly with [`~diffusers.loaders.LoraLoaderMixin.load_lora_weights`] like so:
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lora_model_id = "sayakpaul/civitai-light-shadow-lora"
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lora_filename = "light_and_shadow.safetensors"
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pipeline.load_lora_weights(lora_model_id, weight_name=lora_filename)
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```
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```
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### Supporting Stable Diffusion XL LoRAs trained using the Kohya-trainer
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With this [PR](https://github.com/huggingface/diffusers/pull/4287), there should now be better support for loading Kohya-style LoRAs trained on Stable Diffusion XL (SDXL).
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Here are some example checkpoints we tried out:
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* SDXL 0.9:
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* https://civitai.com/models/22279?modelVersionId=118556
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* https://civitai.com/models/104515/sdxlor30costumesrevue-starlight-saijoclaudine-lora
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* https://civitai.com/models/108448/daiton-sdxl-test
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* https://filebin.net/2ntfqqnapiu9q3zx/pixelbuildings128-v1.safetensors
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* SDXL 1.0:
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* https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/sd_xl_offset_example-lora_1.0.safetensors
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Here is an example of how to perform inference with these checkpoints in `diffusers`:
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```python
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from diffusers import DiffusionPipeline
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import torch
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base_model_id = "stabilityai/stable-diffusion-xl-base-0.9"
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pipeline = DiffusionPipeline.from_pretrained(base_model_id, torch_dtype=torch.float16).to("cuda")
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pipeline.load_lora_weights(".", weight_name="Kamepan.safetensors")
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prompt = "anime screencap, glint, drawing, best quality, light smile, shy, a full body of a girl wearing wedding dress in the middle of the forest beneath the trees, fireflies, big eyes, 2d, cute, anime girl, waifu, cel shading, magical girl, vivid colors, (outline:1.1), manga anime artstyle, masterpiece, offical wallpaper, glint <lora:kame_sdxl_v2:1>"
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negative_prompt = "(deformed, bad quality, sketch, depth of field, blurry:1.1), grainy, bad anatomy, bad perspective, old, ugly, realistic, cartoon, disney, bad propotions"
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generator = torch.manual_seed(2947883060)
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num_inference_steps = 30
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guidance_scale = 7
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image = pipeline(
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prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=num_inference_steps,
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generator=generator, guidance_scale=guidance_scale
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).images[0]
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image.save("Kamepan.png")
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```
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`Kamepan.safetensors` comes from https://civitai.com/models/22279?modelVersionId=118556 .
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If you notice carefully, the inference UX is exactly identical to what we presented in the sections above.
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Thanks to [@isidentical](https://github.com/isidentical) for helping us on integrating this feature.
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### Known limitations specific to the Kohya-styled LoRAs
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* SDXL LoRAs that have both the text encoders are currently leading to weird results. We're actively investigating the issue.
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* When images don't looks similar to other UIs such ComfyUI, it can be beacause of multiple reasons as explained [here](https://github.com/huggingface/diffusers/pull/4287/#issuecomment-1655110736).

‎examples/dreambooth/train_dreambooth_lora.py

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@@ -925,10 +925,10 @@ def load_model_hook(models, input_dir):
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else:
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raise ValueError(f"unexpected save model: {model.__class__}")
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lora_state_dict, network_alpha = LoraLoaderMixin.lora_state_dict(input_dir)
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LoraLoaderMixin.load_lora_into_unet(lora_state_dict, network_alpha=network_alpha, unet=unet_)
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lora_state_dict, network_alphas = LoraLoaderMixin.lora_state_dict(input_dir)
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LoraLoaderMixin.load_lora_into_unet(lora_state_dict, network_alphas=network_alphas, unet=unet_)
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LoraLoaderMixin.load_lora_into_text_encoder(
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lora_state_dict, network_alpha=net 8000 work_alpha, text_encoder=text_encoder_
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lora_state_dict, network_alphas=network_alphas, text_encoder=text_encoder_
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)
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accelerator.register_save_state_pre_hook(save_model_hook)

‎examples/dreambooth/train_dreambooth_lora_sdxl.py

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@@ -825,13 +825,13 @@ def load_model_hook(models, input_dir):
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else:
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raise ValueError(f"unexpected save model: {model.__class__}")
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lora_state_dict, network_alpha = LoraLoaderMixin.lora_state_dict(input_dir)
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LoraLoaderMixin.load_lora_into_unet(lora_state_dict, network_alpha=network_alpha, unet=unet_)
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lora_state_dict, network_alphas = LoraLoaderMixin.lora_state_dict(input_dir)
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LoraLoaderMixin.load_lora_into_unet(lora_state_dict, network_alphas=network_alphas, unet=unet_)
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LoraLoaderMixin.load_lora_into_text_encoder(
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lora_state_dict, network_alpha=network_alpha, text_encoder=text_encoder_one_
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lora_state_dict, network_alphas=network_alphas, text_encoder=text_encoder_one_
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)
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LoraLoaderMixin.load_lora_into_text_encoder(
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lora_state_dict, network_alpha=network_alpha, text_encoder=text_encoder_two_
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lora_state_dict, network_alphas=network_alphas, text_encoder=text_encoder_two_
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)
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accelerator.register_save_state_pre_hook(save_model_hook)

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