diff --git a/model_cards/google/bert2bert_L-24_wmt_en_de/README.md b/model_cards/google/bert2bert_L-24_wmt_en_de/README.md new file mode 100644 index 0000000000..db337ae925 --- /dev/null +++ b/model_cards/google/bert2bert_L-24_wmt_en_de/README.md @@ -0,0 +1,36 @@ +--- +language: +- en +- de +license: apache-2.0 +datasets: +- wmt14 +--- + +# bert2bert_L-24_wmt_en_de EncoderDecoder model + +The model was introduced in +[this paper](https://arxiv.org/abs/1907.12461) by Sascha Rothe, Shashi Narayan, Aliaksei Severyn and first released in [this repository](https://tfhub.dev/google/bertseq2seq/bert24_en_de/1). + +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.* + +```python +from transformers import AutoTokenizer, AutoModelForSeq2SeqLM + +tokenizer = AutoTokenizer.from_pretrained("google/bert2bert_L-24_wmt_en_de", pad_token="", eos_token="", bos_token="") +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?