bert2bert_L-24_wmt_de_en EncoderDecoder model
The model was introduced in this paper by Sascha Rothe, Shashi Narayan, Aliaksei Severyn and first released in this repository.
The model is an encoder-decoder model that was initialized on the
bert-large checkpoints for both the encoder
and decoder and fine-tuned on German to English translation on the WMT dataset, which is linked above.
Disclaimer: The model card has been written by the Hugging Face team.
How to use
You can use this model for translation, e.g.
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/bert2bert_L-24_wmt_de_en", pad_token="<pad>", eos_token="</s>", bos_token="<s>") model = AutoModelForSeq2SeqLM.from_pretrained("google/bert2bert_L-24_wmt_de_en") sentence = "Willst du einen Kaffee trinken gehen mit mir?" input_ids = tokenizer(sentence, return_tensors="pt", add_special_tokens=False).input_ids output_ids = model.generate(input_ids) print(tokenizer.decode(output_ids, skip_special_tokens=True)) # should output # Want to drink a kaffee go with me? .
- Downloads last month
This model can be loaded on the Inference API on-demand.