Create app.py

app.py

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+import tensorflow as tf
+import gradio as gr
+from transformers import GPT2Tokenizer, TFGPT2LMHeadModel
+
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = TFGPT2LMHeadModel.from_pretrained("gpt2",pad_token_id=tokenizer.eos_token_id)
+
+def generate_text(inp):
+    input_ids = tokenizer.encode(inp, return_tensors='tf')
+    beam_output = model.generate(input_ids, max_length=100, num_beams=5, no_repeat_ngram_size=2, early_stopping=True)
+    output = tokenizer.decode(beam_output[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)
+    return ".".join(output.split(".")[:-1]) + "."
+
+input_text = gr.components.Textbox(lines=5, label="Input Text")
+output_text = gr.components.Textbox(label="Output Text")
+
+gr.Interface(generate_text, inputs=input_text, outputs=output_text, title="GPT-2",
+             description="OpenAI's GPT-2 is an unsupervised model that can generate coherent text.\
+              Go ahead and input a sentence and see what it completes it with! Takes around 20s to run").launch(share=True, inline = False)