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import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
device = "cuda"
tokenizer = AutoTokenizer.from_pretrained("NoaiGPT/777")
model = AutoModelForSeq2SeqLM.from_pretrained("NoaiGPT/777").to(device)
def generate_title(text):
input_ids = tokenizer(f'paraphraser: {text}', return_tensors="pt", padding="longest", truncation=True, max_length=64).input_ids.to(device)
outputs = model.generate(
input_ids,
num_beams=4,
num_beam_groups=4,
num_return_sequences=4,
repetition_penalty=10.0,
diversity_penalty=3.0,
no_repeat_ngram_size=2,
temperature=0.8,
max_length=64
)
return tokenizer.batch_decode(outputs, skip_special_tokens=True)
def gradio_generate_title(text):
titles = generate_title(text)
return "\n\n".join(titles)
iface = gr.Interface(
fn=gradio_generate_title,
inputs=gr.Textbox(lines=5, label="Input Text"),
outputs=gr.Textbox(lines=10, label="Generated Titles"),
title="Title Generator",
description="Generate multiple paraphrased titles from input text using NoaiGPT/777 model."
)
iface.launch() |