CoText (2-CC)


Paper: CoTexT: Multi-task Learning with Code-Text Transformer

Authors: Long Phan, Hieu Tran, Daniel Le, Hieu Nguyen, James Anibal, Alec Peltekian, Yanfang Ye

How to use

Supported languages:


For more details, do check out our Github repo.

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("razent/cotext-2-cc")  
model = AutoModelForSeq2SeqLM.from_pretrained("razent/cotext-2-cc")
sentence = "def add(a, b): return a + b"
text =  "python: " + sentence + " </s>"

encoding = tokenizer.encode_plus(text, pad_to_max_length=True, return_tensors="pt")
input_ids, attention_masks = encoding["input_ids"].to("cuda"), encoding["attention_mask"].to("cuda")

outputs = model.generate(
    input_ids=input_ids, attention_mask=attention_masks,

for output in outputs:
    line = tokenizer.decode(output, skip_special_tokens=True, clean_up_tokenization_spaces=True)


    title = "{C}o{T}ex{T}: Multi-task Learning with Code-Text Transformer",
    author = "Phan, Long  and
      Tran, Hieu  and
      Le, Daniel  and
      Nguyen, Hieu  and
      Annibal, James  and
      Peltekian, Alec  and
      Ye, Yanfang",
    booktitle = "Proceedings of the 1st Workshop on Natural Language Processing for Programming (NLP4Prog 2021)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "",
    doi = "10.18653/v1/2021.nlp4prog-1.5",
    pages = "40--47"
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Dataset used to train razent/cotext-2-cc