...

.gitattributes

@@ -1,2 +1,4 @@
-# Auto detect text files and perform LF normalization
-* text=auto
+*.md linguist-vendored=false
+*.md linguist-generated=false
+*.md linguist-documentation=false
+*.md linguist-detectable=true

.gitignore

@@ -1,3 +1,6 @@
+psdenv/
+output/
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

link.bf

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+++++++++++[>+>+++>+++++++>++++++++++<<<<-]>>>>-.++++++++++++++++++.---.+.--------------.-.<<+++++++++++++++.>>+.+++++++++.++++++.---------------.+++++++++++++.++.-------------------.++++++++.+++++.-.--------.+++++++++.++++++.<<+.>>-----------.+++++++++++.-----------------.+++++.<<.>>+.++++++.

main.py

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+import sys
+import os
+
+def main():
+    print("SDXL-Turbo Model Card")
+    print("1. Text-to-image")
+    print("2. Image-to-image")
+
+    choice = input("Select an operation (1 or 2): ")
+
+    if choice == "1":
+        text_to_image_prompt()
+    elif choice == "2":
+        image_to_image_prompt()
+    else:
+        print("Invalid choice. Exiting.")
+        sys.exit()
+
+def text_to_image_prompt():
+    print("Using SDXL-Turbo for Text-to-image:")
+    print("Make sure to install the required packages using:")
+    print("pip install diffusers transformers accelerate --upgrade")
+    print()
+
+    print("Sample prompt:")
+    prompt = input("Enter a text prompt: ")
+
+    text_to_image_code = f"""
+from diffusers import AutoPipelineForText2Image
+import torch
+from PIL import Image
+
+pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
+pipe.to("cuda")
+
+prompt = "{prompt}"
+
+image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+image.save("output/output.jpg")
+    """
+
+    print()
+    print("Generated code snippet:")
+    print(text_to_image_code)
+
+    exec(text_to_image_code)
+
+def image_to_image_prompt():
+    print("Using SDXL-Turbo for Image-to-image:")
+    print("Make sure to install the required packages using:")
+    print("pip install diffusers transformers accelerate --upgrade")
+    print()
+
+    print("Sample prompt:")
+    prompt = input("Enter a text prompt: ")
+
+    image_to_image_code = f"""
+from diffusers import AutoPipelineForImage2Image
+from diffusers.utils import load_image
+import torch
+from PIL import Image
+
+pipe = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
+pipe.to("cuda")
+
+init_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png").resize((512, 512))
+
+prompt = "{prompt}"
+
+image = pipe(prompt, image=init_image, num_inference_steps=2, strength=0.5, guidance_scale=0.0).images[0]
+image.save("output/output.jpg")
+    """
+
+    print()
+    print("Generated code snippet:")
+    print(image_to_image_code)
+
+    exec(image_to_image_code)
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+transformers==4.37.1
+pillow==10.2.0
+
+pip install diffusers transformers accelerate --upgrade

run.bat

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+@echo off
+
+set "VENV_DIR=psdenv"
+
+rem 
+if not exist "%VENV_DIR%" (
+    rem 
+    python -m venv "%VENV_DIR%"
+)
+
+rem 
+call "%VENV_DIR%\Scripts\activate" && python main.py
+
+rem 
+pause

setup.bat

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+@echo off
+python -m venv psdenv
+cmd /k ".\psdenv\Scripts\activate & python main.py"

setup.sh

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+python main.py