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README.md
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---
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license: openrail++
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---
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---
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license: openrail++
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---
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This repository contains offset versions of https://huggingface.co/mhdang/dpo-sdxl-text2image-v1 and https://huggingface.co/mhdang/dpo-sd1.5-text2image-v1.
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These can be added directly to any initialized UNet to inject DPO training into it. See the code below for usage (diffusers only.)
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```py
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def inject_dpo(unet: UNet2DConditionModel, dpo_path: str, strict: bool = False) -> None:
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"""
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Injects DPO weights directly into your UNet.
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Args:
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unet (`UNet2DConditionModel`)
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The initialized UNet from your pipeline.
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dpo_path (`str`)
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The path to the `.safetensors` file downloaded from https://huggingface.co/benjamin-paine/sd-dpo-offsets/.
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Make sure you're using the right file for the right base model.
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strict (`bool`, *optional*)
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Whether or not to raise errors when a weight cannot be applied. Defaults to false.
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"""
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from safetensors import safe_open
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with safe_open(dpo_offset_path, framework="pt", device="cpu") as f:
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for key in f.keys():
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key_parts = key.split(".")
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current_layer = unet
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for key_part in key_parts[:-1]:
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current_layer = getattr(current_layer, key_part, None)
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if current_layer is None:
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break
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if current_layer is None:
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if strict:
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raise IOError(f"Couldn't find a layer to inject key {key} in.")
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continue
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layer_param = getattr(current_layer, key_parts[-1], None)
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if layer_param is None:
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if strict:
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raise IOError(f"Couldn't get weighht parameter for key {key}")
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layer_param.data += f.get_tensor(key)
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```
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Now you can use this function like so:
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```py
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from diffusers import StableDiffusionPipeline
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import huggingface_hub
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import torch
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# load sdv15 pipeline
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model_id = "Lykon/dreamshaper-8"
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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# download DPO offsets
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dpo_path = huggingface_hub.hf_hub_download("painebenjamin/sd-dpo-offsets", "sd_v15_unet_dpo_offset.safetensors")
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# inject
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inject_dpo(pipe.unet, dpo_path)
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# make image
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prompt = "Two cats playing chess on a tree branch"
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image = pipe(prompt, guidance_scale=7.5).images[0]
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image.save("cats_playing_chess.png")
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```
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Or for XL:
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```py
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from diffusers import StableDiffusionXLPipeline
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# load sdxl pipeline
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model_id = "Lykon/dreamshaper-xl-1-0"
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pipe = StableDiffusionXLPipeline.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16")
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# download DPO offsets
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dpo_path = huggingface_hub.hf_hub_download("painebenjamin/sd-dpo-offsets", "sd_xl_unet_dpo_offset.safetensors")
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# inject
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inject_dpo(pipe.unet, dpo_path)
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# make image
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prompt = "Two cats playing chess on a tree branch"
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image = pipe(prompt, guidance_scale=7.5).images[0]
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image.save("cats_playing_chess.png")
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```
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