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SafeTensors format using transformers 4.40.1. The goal of this reupload is to prevent older models that are still relevant baselines from becoming stale as a result of changes in HuggingFace. Additionally, I may include minor corrections, such as model max length configuration.1"go"
2"java"
3"javascript"
4"php"
5"python"
6"ruby"1from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
2
3tokenizer = AutoTokenizer.from_pretrained("razent/cotext-1-cc")
4model = AutoModelForSeq2SeqLM.from_pretrained("razent/cotext-1-cc")
5
6sentence = "def add(a, b): return a + b"
7text = "python: " + sentence + " </s>"
8
9encoding = tokenizer.encode_plus(text, pad_to_max_length=True, return_tensors="pt")
10input_ids, attention_masks = encoding["input_ids"].to("cuda"), encoding["attention_mask"].to("cuda")
11
12outputs = model.generate(
13 input_ids=input_ids, attention_mask=attention_masks,
14 max_length=256,
15 early_stopping=True
16)
17
18for output in outputs:
19 line = tokenizer.decode(output, skip_special_tokens=True, clean_up_tokenization_spaces=True)
20 print(line)@inproceedings{phan-etal-2021-cotext,
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)",
year = "2021",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.nlp4prog-1.5",
doi = "10.18653/v1/2021.nlp4prog-1.5",
pages = "40--47"
}