ielabgroup/BiTAG-t5-large

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model = AutoModelForSeq2SeqLM.from_pretrained("ArvinZhuang/BiTAG-t5-large")
tokenizer = AutoTokenizer.from_pretrained("ArvinZhuang/BiTAG-t5-large")

text = "abstract: [your abstract]"  # use 'title:' as the prefix for title_to_abs task.
input_ids = tokenizer.encode(text, return_tensors='pt')

outputs = model.generate(
    input_ids,
    do_sample=True,
    max_length=500,
    top_p=0.9,
    top_k=20,
    temperature=1,
    num_return_sequences=10,
)

print("Output:\n" + 100 * '-')
for i, output in enumerate(outputs):
    print("{}: {}".format(i+1, tokenizer.decode(output, skip_special_tokens=True)))

GitHub: https://github.com/ArvinZhuang/BiTAG