from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("flax-community/t5-large-wikisplit")
model = AutoModelForSeq2SeqLM.from_pretrained("flax-community/t5-large-wikisplit")
complex_sentence = "This comedy drama is produced by Tidy , the company she co-founded in 2008 with her husband David Peet , who is managing director ."
sample_tokenized = tokenizer(complex_sentence, return_tensors="pt")
answer = model.generate(sample_tokenized['input_ids'], attention_mask = sample_tokenized['attention_mask'], max_length=256, num_beams=5)
gene_sentence = tokenizer.decode(answer[0], skip_special_tokens=True)
gene_sentence
"""
Output:
This comedy drama is produced by Tidy. She co-founded Tidy in 2008 with her husband David Peet, who is managing director.
"""

Datasets:

Wiki_Split

Current Basline from paper

Our Results:

Model	Exact	SARI	BLEU
t5-base-wikisplit	17.93	67.5438	76.9
t5-v1_1-base-wikisplit	18.1207	67.4873	76.9478
byt5-base-wikisplit	11.3582	67.2685	73.1682
t5-large-wikisplit	18.6632	68.0501	77.1881