Update app.py

app.py

@@ -1,16 +1,10 @@
-from transformers import GPT2LMHeadModel,GPT2Tokenizer
+from transformers import pipeline, set_seed
 import gradio as grad
-
-mdl = GPT2LMHeadModel.from_pretrained('gpt2')
-gpt2_tkn=GPT2Tokenizer.from_pretrained('gpt2')
+gpt2_pipe = pipeline('text-generation', model='distilgpt2')
+set_seed(42)
 
 def generate(starting_text):
-    tkn_ids = gpt2_tkn.encode(starting_text, return_tensors = 'pt')
-    gpt2_tensors = mdl.generate(tkn_ids,max_length=100,no_repeat_ngram_size=True,num_beams=3,do_sample=True,temperatue=0.1)
-    response=""
-    #response = gpt2_tensors
-    for i, x in enumerate(gpt2_tensors):
-       response=response+f"{i}: {gpt2_tkn.decode(x, skip_special_tokens=True)}"
+    response= gpt2_pipe(starting_text, max_length=20, num_return_sequences=5)
     return response
 txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
 out=grad.Textbox(lines=1, label="Generated Text")