wip

app.py

@@ -1,7 +1,25 @@
 import gradio as gr
+from diffusers import DiffusionPipeline
+import torch
 
-def greet(name):
-    return "Hello " + name + "!!"
+def get_device():
+  if torch.cuda.is_available():
+    return "cuda"
+  else:
+    return "cpu"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+def generate_image(prompt):
+  pipe_id = "SG161222/Realistic_Vision_V6.0_B1_noVAE"
+  pipe = DiffusionPipeline.from_pretrained(pipe_id, torch_dtype=torch.float16).to("cuda")
+  pipe.load_lora_weights("timdpaep/t1m")
+  prompt = "professional photo, closeup photo of t1mLora, wearing black sweater, nature, gloomy, cloudy weather, bokeh <lora:t1m01:1>"
+
+  lora_scale= 0.9
+  image = pipe(
+    prompt, num_inference_steps=10, cross_attention_kwargs={"scale": lora_scale}, generator=torch.manual_seed(0)
+  ).to(get_device()).images[0]
+  return image
+
+
+iface = gr.Interface(fn=generate_image, inputs="textbox", outputs="image")
 iface.launch()

requirements.txt

@@ -0,0 +1,5 @@
+gradio
+diffusers
+accelerate
+transformers
+torch