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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) |