Update app.py

app.py

@@ -1,37 +1,19 @@
-import tensorflow as tf
-from transformers import AutoTokenizer, TFGPT2LMHeadModel
 import gradio as gr 
 
-review_model = TFGPT2LMHeadModel.from_pretrained("kmkarakaya/turkishReviews-ds")
-review_tokenizer = AutoTokenizer.from_pretrained("kmkarakaya/turkishReviews-ds")
+title="Review Generator"
+description= "Generate a review in Turkish by providing a prompt. Generation takes 15 seconds on average."
+article = "<p style='text-align: center'><a href='https://youtube.com/playlist?list=PLQflnv_s49v9d9w-L0S8XUXXdNks7vPBL' target='_blank'>Full Code is here: </a></p>"                    
+examples=["Bir hafta önce aldığım cep telefonu",
+          "Tatil için rezervasyon yaptırdım.",
+          "Henüz alalı bir"]                   
 
-def generate_review(prompt):
 
-  input_ids = review_tokenizer.encode(prompt, return_tensors='tf')
-  context_length = 40
-  output = review_model.generate(
-      input_ids, 
-      do_sample=True,
-      max_length=context_length, 
-      top_k=10,
-      no_repeat_ngram_size=2, 
-      early_stopping=True
-  )
-
-  return(review_tokenizer.decode(output[0], skip_special_tokens=True))
-  
- demo = gr.Interface(fn=generate_review, 
-                    inputs="text", 
-                    outputs="text",
-                    examples=[
-                              "Bir hafta önce aldığım cep telefonu",
-                              "Tatil için rezervasyon yaptırdım.",
-                              "Henüz alalı bir"],
-                    title="Review Generator",
-                    description= """
-                    Generate a review in Turkish by providing a prompt.
-                    Generation takes 15 seconds on average.
-                    Full Code is here: https://youtube.com/playlist?list=PLQflnv_s49v9d9w-L0S8XUXXdNks7vPBL
-                    """
-                    )
-demo.launch()
+gr.Interface.load(
+    "kmkarakaya/turkishReviews-ds",
+    inputs=gr.Textbox(lines=5, label="Input Text"),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+    enable_queue=True,
+).launch()