Nguyen17/Chatbot_Mining

1import gradio as gr2import torch3from transformers import GPT2Tokenizer, GPT2LMHeadModel4 5 6tokenizer = GPT2Tokenizer.from_pretrained('NlpHUST/gpt2-vietnamese')7model = GPT2LMHeadModel.from_pretrained('NlpHUST/gpt2-vietnamese')8# max_length = 1009 10 11def run(text, intensity):12    res="Tham khảo NlpHUST model  \n  \n  \n"13    max_length=intensity14        15    input_ids = tokenizer.encode(text, return_tensors='pt')16    sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,17                                   do_sample=True,18                                   max_length=max_length,19                                   min_length=5,20                                   top_k=40,21                                   num_beams=5,22                                   early_stopping=True,23                                   no_repeat_ngram_size=2,24                                   num_return_sequences=2)25    26    for i, sample_output in enumerate(sample_outputs):27        res +="Mẫu số {}\n \n{}".format(i+1, tokenizer.decode(sample_output.tolist()))28        res +='\n \n \n \n'29    return res30 31# demo = gr.Interface(32#     fn=run,33#     inputs=["text", "slider"],34#     outputs=["text"],35# )36 37demo = gr.Interface(fn=run,38                    inputs=[gr.Textbox(label="Nhập vào nội dung input",value="Con đường xưa em đi"),gr.Slider(label="Độ dài output muốn tạo ra", value=20, minimum=10, maximum=100, step=2)],39                    outputs=gr.Textbox(label="Output"),  # <-- Number of output components: 140                    )41 42demo.launch()43 44 45 46 47 48 49 50 51