Duplicate from diffusers/sdxl-instructpix2pix-768

Co-authored-by: Sayak Paul <sayakpaul@users.noreply.huggingface.co>

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README.md

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+---
+license: openrail++
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers
+- instruct-pix2pix
+inference: false
+datasets:
+- timbrooks/instructpix2pix-clip-filtered
+---
+
+# SDXL InstructPix2Pix (768768)
+
+Instruction fine-tuning of [Stable Diffusion XL (SDXL)](https://hf.co/papers/2307.01952) à la [InstructPix2Pix](https://huggingface.co/papers/2211.09800). Some results below:
+
+
+**Edit instruction**: *"Turn sky into a cloudy one"*
+
+![](https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/sdxl-instructpix2pix-release/0_0_mountain_gs%403.0_igs%401.5_steps%4050.png)
+
+**Edit instruction**: *"Make it a picasso painting"*
+
+![](https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/sdxl-instructpix2pix-release/1_1_cyborg_gs%403.0_igs%401.5_steps%4050.png)
+
+**Edit instruction**: *"make the person older"*
+
+![](https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/sdxl-instructpix2pix-release/image_three_2.png)
+
+## Usage in 🧨 diffusers
+
+Make sure to install the libraries first:
+
+```bash 
+pip install accelerate transformers
+pip install git+https://github.com/huggingface/diffusers
+```
+
+```python 
+import torch
+from diffusers import StableDiffusionXLInstructPix2PixPipeline
+from diffusers.utils import load_image
+
+resolution = 768
+image = load_image(
+    "https://hf.co/datasets/diffusers/diffusers-images-docs/resolve/main/mountain.png"
+).resize((resolution, resolution))
+edit_instruction = "Turn sky into a cloudy one"
+
+pipe = StableDiffusionXLInstructPix2PixPipeline.from_pretrained(
+    "diffusers/sdxl-instructpix2pix-768", torch_dtype=torch.float16
+).to("cuda")
+
+edited_image = pipe(
+    prompt=edit_instruction,
+    image=image,
+    height=resolution,
+    width=resolution,
+    guidance_scale=3.0,
+    image_guidance_scale=1.5,
+    num_inference_steps=30,
+).images[0]
+edited_image.save("edited_image.png")
+```
+
+To know more, refer to the [documentation](https://huggingface.co/docs/diffusers/main/en/api/pipelines/pix2pix). 
+
+🚨 Note that this checkpoint is experimental in nature and there's a lot of room for improvements. Please use the "Discussions" tab of this repository to open issues and discuss. 🚨
+
+## Training
+We fine-tuned SDXL using the InstructPix2Pix training methodology for 15000 steps using a fixed learning rate of 5e-6 on an image resolution of 768x768. 
+
+Our training scripts and other utilities can be found [here](https://github.com/sayakpaul/instructpix2pix-sdxl/tree/b9acc91d6ddf1f2aa2f9012b68216deb40e178f3) and they were built on top of our [official training script](https://huggingface.co/docs/diffusers/main/en/training/instructpix2pix). 
+
+Our training logs are available on Weights and Biases [here](https://wandb.ai/sayakpaul/instruct-pix2pix-sdxl-new/runs/sw53gxmc). Refer to this link for details on all the hyperparameters. 
+
+### Training data
+We used this dataset: [timbrooks/instructpix2pix-clip-filtered](https://huggingface.co/datasets/timbrooks/instructpix2pix-clip-filtered).
+
+### Compute
+one 8xA100 machine
+
+### Batch size
+Data parallel with a single gpu batch size of 8 for a total batch size of 32.
+
+### Mixed precision
+FP16

model_index.json

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+{
+  "_class_name": "StableDiffusionXLInstructPix2PixPipeline",
+  "_diffusers_version": "0.21.0.dev0",
+  "_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0",
+  "force_zeros_for_empty_prompt": true,
+  "scheduler": [
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+    "EulerDiscreteScheduler"
+  ],
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+    "CLIPTextModel"
+  ],
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+    "CLIPTextModelWithProjection"
+  ],
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+  ],
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+  ],
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+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

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+  "prediction_type": "epsilon",
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+  "use_karras_sigmas": false
+}

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