Create app.py

app.py

@@ -0,0 +1,25 @@
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+import gradio as gr
+
+model_name = "gpt2"
+model = GPT2LMHeadModel.from_pretrained(model_name)
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+
+def generate(text):
+    token_ids = tokenizer.encode(text, return_tensors="pt")
+    gpt2_tensors = model.generate(token_ids, max_length=200, 
+                                  no_repeat_ngram_size=True, 
+                                  num_beams=3,
+                                  do_sample=True,
+                                  temperature=1.5
+                                 )
+    
+    #response= gpt2_tensors
+    response = ""
+    for i, x in enumerate(gpt2_tensors):
+        response += f"{i}: {tokenizer.decode(x, skip_special_tokens=True)}"
+    return response
+
+in_text = gr.Textbox(lines=1, label="English", placeholder="English text here")
+out = gr.Textbox(lines=1, label="Generated tensors")
+gr.Interface(generate, inputs=in_text, outputs=out).launch()