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#---------------------AI Paraphraser - iFrame code --------------
# With direct model load
#----------------------------------------------------------------
#----------------------------------------------------------------
import transformers
import gradio as gr
import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("humarin/chatgpt_paraphraser_on_T5_base")
model = AutoModelForSeq2SeqLM.from_pretrained("humarin/chatgpt_paraphraser_on_T5_base")
def paraphrase(
Content_to_Rephrase,
num_beams=5,
num_beam_groups=5,
num_return_sequences=5,
repetition_penalty=10.0,
diversity_penalty=3.0,
no_repeat_ngram_size=2,
max_length=5000
):
input_ids = tokenizer(
f'paraphrase: {Content_to_Rephrase}',
return_tensors="pt", padding="longest",
max_length=max_length,
truncation=True,
).input_ids
outputs = model.generate(
input_ids, repetition_penalty=repetition_penalty,
num_return_sequences=num_return_sequences, no_repeat_ngram_size=no_repeat_ngram_size,
num_beams=num_beams, num_beam_groups=num_beam_groups,
max_length=max_length, diversity_penalty=diversity_penalty
)
res = tokenizer.batch_decode(outputs, skip_special_tokens=True)
res1 = res [0]
res2 = res [1]
res3 = res [3]
res4 = res [4]
return res1, res2, res3
output1 = gr.Textbox(label="Rephrased: Option 1")
output2 = gr.Textbox(label="Rephrased: Option 2")
output3 = gr.Textbox(label="Rephrased: Option 3")
iface = gr.Interface(fn=paraphrase,
inputs=["text"],
outputs=[output1, output2, output3],
title="Free AI Sentence Rephraser",
description="<ul><li>Paste text in the input box and press 'Submit'.</li><li>Max length: ~35 words (larger content is summarized)</li><li>The rephrased sentences *may not* be better than the original input.</li><li>Model 'humarin' pre-trained by ChatGPT. Temp = 0.7</li></ul>",
examples=[
["With the humble is wisdom."],
["Hatred stirs up strife."],
["The way of a fool is right in his own eyes."],
["Righteousness leads to life."],
],
cache_examples=True,
)
iface.launch() |