Update app.py

app.py

@@ -1,7 +1,45 @@
 import gradio as gr
+import torch
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+
+tokenizer = GPT2Tokenizer.from_pretrained('NlpHUST/gpt2-vietnamese')
+model = GPT2LMHeadModel.from_pretrained('NlpHUST/gpt2-vietnamese')
+# max_length = 100
+
+
+def run(text, intensity):
+    res=""
+    max_length=intensity
+    input_ids = tokenizer.encode(text, return_tensors='pt')
+    sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
+                                   do_sample=True,
+                                   max_length=max_length,
+                                   min_length=max_length,
+                                   top_k=40,
+                                   num_beams=5,
+                                   early_stopping=True,
+                                   no_repeat_ngram_size=2,
+                                   num_return_sequences=3)
+    
+    for i, sample_output in enumerate(sample_outputs):
+        res +="Generated text {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist()))
+        res +='\n---'
+    return res
+
+demo = gr.Interface(
+    fn=run,
+    inputs=["text", "slider"],
+    outputs=["text"],
+)
+
+demo.launch()
+
+
+
+
+
+
+
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()