Update app.py

app.py

@@ -1,38 +1,31 @@
 import gradio as gr
-from PIL import Image
-import torch
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
-model2 = torch.hub.load(
-    "AK391/animegan2-pytorch:main",
-    "generator",
-    pretrained=True,
-    progress=False
-)
-model1 = torch.hub.load("AK391/animegan2-pytorch:main", "generator", pretrained="face_paint_512_v1")
-face2paint = torch.hub.load(
-    'AK391/animegan2-pytorch:main', 'face2paint', 
-    size=512,side_by_side=False
-)
+model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large")
+tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-large")
 
 def inference(img, ver):
-    if ver == 'version 2 (🔺 robustness,🔻 stylization)':
-        out = face2paint(model2, img)
+    if ver == "Hidden Identity 1":
+        out = "Michael Jackson"
     else:
-        out = face2paint(model1, img)
+        out = "Brad Pitt"
     return out
+    
+def generate(text,guess):
+    inputs =  tokenizer(f"Answer with yes or no the following question about {guess}: {text}?", return_tensors="pt")
+    return model.generate(**inputs)[0]
 
-title = "Portrait of your Pet"
-description = "Demo for Pet Portrait. To use it, simply upload your image, or click one of the examples to load them."
-article = "Github Repo Pytorch "
-examples=[['groot.jpeg','version 2 (🔺 robustness,🔻 stylization)'],['gongyoo.jpeg','version 2 (🔺 robustness,🔻 stylization)']]
+examples = [
+    ["Is it dead?"],
+    ["Is it a female?"],
+]
 
 demo = gr.Interface(
-    fn=inference, 
-    inputs=[gr.inputs.Image(type="pil"),gr.inputs.Radio(['version 2 (🔺 robustness,🔻 stylization)'], type="value", default='version 2 (🔺 robustness,🔻 stylization)', label='version')], 
-    outputs=gr.outputs.Image(type="pil"),
-    title=title,
-    description=description,
-    article=article,
-    examples=examples)
+    fn=generate,
+    inputs=[gr.inputs.Textbox(lines=5, label="Input Text"),
+    		gr.inputs.Radio("Hidden Identity 1", type="value", default='Hidden Identity 1', label='Hidden identity')],
+    outputs=gr.outputs.Textbox(label="Generated Text"),
+    examples=examples
+)
 
 demo.launch()