Transformers
PyTorch
Chinese
marian
text2text-generation
Seq2SeqLM
古文
文言文
中国古代官职翻译
ancient
classical
Instructions to use cbdb/ClassicalChineseOfficeTitleTranslation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cbdb/ClassicalChineseOfficeTitleTranslation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cbdb/ClassicalChineseOfficeTitleTranslation") model = AutoModelForSeq2SeqLM.from_pretrained("cbdb/ClassicalChineseOfficeTitleTranslation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e015002cb43737d4c9a326c7cd196cbf3bcdd0cf27b3a36a23fb0ddfab6cfbd
- Size of remote file:
- 310 MB
- SHA256:
- fd95090d48323061e3189b76b9c800199fed70f4a87d8883cd6597e3ae1e1c5a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.