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Update README.md

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@@ -54,6 +54,42 @@ image = pipe(prompt, num_inference_steps=4, guidance_scale=0).images[0]
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  <img style="width:400px;" src="images/raccoon.png">
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  </p>
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  # Training Details
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  The model was trained for 20k iterations on 4 H100 GPUs (representing approximately a total of 176 GPU hours of training). Please refer to the [paper](http://arxiv.org/abs/2406.02347) for further parameters details.
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  <img style="width:400px;" src="images/raccoon.png">
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  </p>
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+ # Combining Flash Diffusion with Existing LoRAs 🎨
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+
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+ FlashSDXL can also be combined with existing LoRAs to unlock few steps generation in a **training free** manner. It can be integrated straight to Hugging Face pipelines. See an example below.
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+
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+ ```python
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+ from diffusers import DiffusionPipeline, LCMScheduler
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+ import torch
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+
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+ flash_lora_id = "jasperai/flash-sdxl"
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+
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+ # Load Pipeline
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+ pipe = DiffusionPipeline.from_pretrained(
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+ "stabilityai/stable-diffusion-xl-base-1.0",
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+ variant="fp16"
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+ )
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+
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+ # Set scheduler
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+ pipe.scheduler = LCMScheduler.from_config(
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+ pipe.scheduler.config
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+ )
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+
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+ # Load LoRAs
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+ pipe.load_lora_weights(flash_lora_id, adapter_name="flash")
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+ pipe.load_lora_weights("TheLastBen/Papercut_SDXL", adapter_name="paper")
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+
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+ pipe.set_adapters(["flash", "paper"], adapter_weights=[1.0, 1.0])
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+ pipe.to(device="cuda", dtype=torch.float16)
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+
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+ prompt = "papercut, a cute corgi"
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+
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+ image = pipe(prompt, num_inference_steps=4, guidance_scale=0).images[0]
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+ ```
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+ <p align="center">
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+ <img style="width:400px;" src="images/corgi.jpg">
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+ </p>
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+
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  # Training Details
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  The model was trained for 20k iterations on 4 H100 GPUs (representing approximately a total of 176 GPU hours of training). Please refer to the [paper](http://arxiv.org/abs/2406.02347) for further parameters details.
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