Create app.py

app.py

@@ -0,0 +1,15 @@
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+trained_tokenizer = GPT2Tokenizer.from_pretrained("Kumarkishalaya/GPT-2-next-word-prediction")
+trained_model = GPT2LMHeadModel.from_pretrained("Kumarkishalaya/GPT-2-next-word-prediction")
+untrained_model = GPT2Tokenizer.from_pretrained("gpt2")
+untrained_tokenizer = ("gpt2")
+
+def generate(commentary_text):
+    input_ids = trained_tokenizer(commentary_text, return_tensors="pt")
+    input_ids = input_ids['input_ids'].to(device)
+    output = trained_model.generate(input_ids, max_length=60, num_beams=5, do_sample=False)
+    return tokenizer_finetuned.decode(output[0])
+
+demo = gr.Interface(fn=generate, inputs="text", outputs="text")
+demo.launch()