Update app.py

app.py

@@ -1,26 +1,37 @@
 import gradio as gr
-import diffusers
-import streamlit as st
-device = "cpu"
-from diffusers import StableDiffusionPipeline
-pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", revision = "fp16", use_auth_token = st.secrets["USER_TOKEN"])
-pipe = pipe.to("cpu")
-from PIL import Image
-import torch
-def StableDiffusionPipeline (prompt, Guide, iSteps, seed):
-    generator = torch.Generator("cpu").manual_seed(seed)
-    image = pipe(prompt, num_inference_steps = iSteps, guidence_scale = Guide).images[0]
-    return image
-iface = gr.Interface(fn = StableDiffusionPipeline, inputs = [
-    gr.Textbox(label = 'Prompt Input Text'),
-    gr.Slider(2, 15, value = 7, label = 'Guidence Scale'),
-    gr.Slider(10, 100, value = 25, step = 1, label = 'Number of Iterations'),
-    gr.Slider(
-        label = "Seed",
-        minimum = 0,
-        maximum = 2147483647,
-        step = 1,
-        randomize = True)
-    ],
-    outputs = 'image')
-iface.launch()
+
+models =["CompVis/stable-diffusion-v1-4", "runwayml/stable-diffusion-v1-5", "stabilityai/stable-diffusion-2-1", "stabilityai/stable-diffusion-2-1-base"]
+
+model_1=models[1]
+model_2=models[2]
+model_3=models[3]
+model_4=models[4]
+
+gr.Interface.load(f"models/{model_1}",live=False,preprocess=True, postprocess=False).launch()
+
+
+#import diffusers
+#import streamlit as st
+#device = "cpu"
+#from diffusers import StableDiffusionPipeline
+#pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", revision = "fp16", use_auth_token = st.secrets["USER_TOKEN"])
+#pipe = pipe.to("cpu")
+#from PIL import Image
+#import torch
+#def StableDiffusionPipeline (prompt, Guide, iSteps, seed):
+#    generator = torch.Generator("cpu").manual_seed(seed)
+#    image = pipe(prompt, num_inference_steps = iSteps, guidence_scale = Guide).images[0]
+#    return image
+#iface = gr.Interface(fn = StableDiffusionPipeline, inputs = [
+#    gr.Textbox(label = 'Prompt Input Text'),
+#    gr.Slider(2, 15, value = 7, label = 'Guidence Scale'),
+#    gr.Slider(10, 100, value = 25, step = 1, label = 'Number of Iterations'),
+#    gr.Slider(
+#        label = "Seed",
+#        minimum = 0,
+#        maximum = 2147483647,
+#        step = 1,
+#        randomize = True)
+#    ],
+#    outputs = 'image')
+#iface.launch()