Back to all models
translation mask_token:
Query this model
🔥 This model is currently loaded and running on the Inference API. ⚠️ This model could not be loaded by the inference API. ⚠️ This model can be loaded on the Inference API on-demand.
JSON Output
API endpoint  

⚡️ Upgrade your account to access the Inference API

Share Copied link to clipboard

Monthly model downloads

google/bert2bert_L-24_wmt_en_de google/bert2bert_L-24_wmt_en_de
38 downloads
last 30 days

pytorch

tf

Contributed by

Google AI company
3 team members · 54 models

How to use this model directly from the 🤗/transformers library:

			
Copy to clipboard
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/bert2bert_L-24_wmt_en_de") model = AutoModelForSeq2SeqLM.from_pretrained("google/bert2bert_L-24_wmt_en_de")

bert2bert_L-24_wmt_en_de 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 English to German 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_en_de", pad_token="<pad>", eos_token="</s>", bos_token="<s>")
model = AutoModelForSeq2SeqLM.from_pretrained("google/bert2bert_L-24_wmt_en_de")

sentence = "Would you like to grab a coffee with me this week?"

input_ids = tokenizer(sentence, return_tensors="pt", add_special_tokens=False).input_ids
output_ids = model.generate(input_ids)[0]
print(tokenizer.decode(output_ids, skip_special_tokens=True))
# should output
# Möchten Sie diese Woche einen Kaffee mit mir schnappen?