Duplicate from Manjushri/SD-2.1-CPU

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README.md

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+---
+title: SD 2.1 CPU
+emoji: 🔥
+colorFrom: red
+colorTo: red
+sdk: gradio
+sdk_version: 3.11.0
+app_file: app.py
+pinned: false
+license: mit
+duplicated_from: Manjushri/SD-2.1-CPU
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import torch
+import numpy as np
+import modin.pandas as pd
+from PIL import Image
+from diffusers import DiffusionPipeline #EulerDiscreteScheduler
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+#scheduler = EulerDiscreteScheduler.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="scheduler", prediction_type="v_prediction")
+pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1", safety_checker=None)
+pipe = pipe.to(device)
+
+def genie (prompt, negative_prompt, scale, steps, seed):
+     generator = torch.Generator(device=device).manual_seed(seed)
+     images = pipe(prompt, negative_prompt=negative_prompt, width=768, height=768, num_inference_steps=steps, guidance_scale=scale, num_images_per_prompt=1, generator=generator).images[0]
+     return images
+    
+gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit.'), gr.Textbox(label='What you Do Not want the AI to generate.'), gr.Slider(1, 25, 10), gr.Slider(1, maximum=20, value=10, step=1), gr.Slider(minimum=1, step=1, maximum=999999999999999999, randomize=True)], outputs='image', title="Stable Diffusion 2.1 CPU", description="SD 2.1 CPU. <b>WARNING:</b> Extremely Slow. 130s/Iteration. Expect 14-28mins an image for 10-20 iterations respectively.", article = "Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=True)

requirements.txt

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+-f --extra-index-url https://download.pytorch.org/whl/cu116
+torch
+torchvision
+git+https://github.com/huggingface/diffusers
+transformers
+accelerate
+ftfy
+xformers
+modin[all]