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--- |
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base_model: stabilityai/stable-diffusion-xl-base-1.0 |
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library_name: diffusers |
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license: openrail++ |
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tags: |
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- text-to-image |
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- text-to-image |
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- diffusers-training |
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- diffusers |
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- lora |
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- template:sd-lora |
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- stable-diffusion-xl |
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- stable-diffusion-xl-diffusers |
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datasets: |
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- data-is-better-together/open-image-preferences-v1-binarized |
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language: |
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- en |
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pipeline_tag: text-to-image |
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widget: |
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- text: An hyperrealistic astronaut riding a green horse |
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output: |
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url: images/example_p8cnk74hq.png |
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--- |
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# Low Rank Adapted Supervised Fine Tuned Stable Diffusion XL |
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## Comparison |
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| Prompt | SDXL | Fine Tuned | |
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| :--: | :--: | :--: | |
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| a boat in the canals of Venice, painted in gouache with soft, flowing brushstrokes and vibrant, translucent colors, capturing the serene reflection on the water under a misty ambiance, with rich textures and a dynamic perspective |  |  | |
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| Grainy shot of a robot cooking in the kitchen, with soft shadows and nostalgic film texture. |  |  | |
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## Model description |
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These are ariG23498/open-image-preferences-v1-sdxl-lora LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. |
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The weights were trained using [DreamBooth](https://github.com/ariG23498/diffusers/blob/aritra/sdxl-lora/examples/dreambooth/train_dreambooth_lora_sdxl.py) using the |
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[open-image-preferences-v1-binarized](https://huggingface.co/datasets/data-is-better-together/open-image-preferences-v1-binarized) dataset. |
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## Use with `diffusers` |
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```py |
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from diffusers import AutoPipelineForText2Image |
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import torch |
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pipeline = AutoPipelineForText2Image.from_pretrained( |
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"stabilityai/stable-diffusion-xl-base-1.0", |
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torch_dtype=torch.bfloat16 |
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).to('cuda') |
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pipeline.load_lora_weights('ariG23498/open-image-preferences-v1-sdxl-lora', weight_name='pytorch_lora_weights.safetensors') |
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prompt = "ENTER PROMPT" |
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image = pipeline(prompt).images[0] |
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``` |
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## Command to train the model |
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```shell |
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!accelerate launch examples/dreambooth/train_dreambooth_lora_sdxl.py \ |
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--pretrained_model_name_or_path "stabilityai/stable-diffusion-xl-base-1.0" \ |
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--dataset_name "data-is-better-together/open-image-preferences-v1-binarized" \ |
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--hub_model_id "ariG23498/open-image-preferences-v1-sdxl-lora" \ |
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--push_to_hub \ |
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--output_dir "open-image-preferences-v1-sdxl-lora" \ |
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--image_column "chosen" \ |
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--caption_column "prompt" \ |
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--mixed_precision="bf16" \ |
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--resolution=1024 \ |
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--train_batch_size=1 \ |
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--repeats=1 \ |
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--report_to="wandb"\ |
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--gradient_accumulation_steps=1 \ |
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--gradient_checkpointing \ |
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--learning_rate=1.0 \ |
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--text_encoder_lr=1.0 \ |
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--optimizer="prodigy"\ |
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--lr_scheduler="constant" \ |
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--lr_warmup_steps=0 \ |
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--rank=8 \ |
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--checkpointing_steps=2000 \ |
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--seed="0" |
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``` |