Ptt5 V2 Base

🚀 ptt5-v2-base

ptt5-v2模型是專門為葡萄牙語定製的預訓練T5模型，它基於谷歌原始的檢查點繼續訓練，模型大小從t5-small到t5-3B不等。這些檢查點被用於訓練葡萄牙語的MonoT5重排器，你可以在它們的HuggingFace集合中找到。如需瞭解更多關於預訓練過程的信息，請參考我們的論文ptt5-v2: A Closer Look at Continued Pretraining of T5 Models for the Portuguese Language。

🚀 快速開始

模型信息

模型介紹

ptt5-v2模型是專門為葡萄牙語定製的預訓練T5模型，它在谷歌原始檢查點的基礎上繼續訓練，模型大小涵蓋從t5-small到t5-3B。這些檢查點用於訓練葡萄牙語的MonoT5重排器，可在其HuggingFace集合中找到。關於預訓練過程的更多信息，請參考我們的論文ptt5-v2: A Closer Look at Continued Pretraining of T5 Models for the Portuguese Language。

💻 使用示例

基礎用法

from transformers import T5Tokenizer, T5ForConditionalGeneration

tokenizer = T5Tokenizer.from_pretrained("unicamp-dl/ptt5-v2-base")
model = T5ForConditionalGeneration.from_pretrained("unicamp-dl/ptt5-v2-base")

📄 許可證

本項目採用apache-2.0許可證。

📚 詳細文檔

引用信息

如果你使用了我們的模型，請按照以下格式進行引用：

@article{piau2024ptt5v2,
      title={ptt5-v2: A Closer Look at Continued Pretraining of T5 Models for the Portuguese Language}, 
      author={Marcos Piau and Roberto Lotufo and Rodrigo Nogueira},
      year={2024},
      eprint={2406.10806},
      archivePrefix={arXiv},
      primaryClass={id='cs.CL' full_name='Computation and Language' is_active=True alt_name='cmp-lg' in_archive='cs' is_general=False description='Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.'}
}