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--- |
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language: |
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- en |
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- de |
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license: apache-2.0 |
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datasets: |
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- wmt14 |
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tags: |
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- translation |
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--- |
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# bert2bert_L-24_wmt_de_en EncoderDecoder model |
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The model was introduced in |
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[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_de_en/1). |
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The model is an encoder-decoder model that was initialized on the `bert-large` checkpoints for both the encoder |
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and decoder and fine-tuned on German to English translation on the WMT dataset, which is linked above. |
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Disclaimer: The model card has been written by the Hugging Face team. |
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## How to use |
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You can use this model for translation, *e.g.* |
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```python |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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tokenizer = AutoTokenizer.from_pretrained("google/bert2bert_L-24_wmt_de_en", pad_token="<pad>", eos_token="</s>", bos_token="<s>") |
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model = AutoModelForSeq2SeqLM.from_pretrained("google/bert2bert_L-24_wmt_de_en") |
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sentence = "Willst du einen Kaffee trinken gehen mit mir?" |
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input_ids = tokenizer(sentence, return_tensors="pt", add_special_tokens=False).input_ids |
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output_ids = model.generate(input_ids)[0] |
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print(tokenizer.decode(output_ids, skip_special_tokens=True)) |
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# should output |
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# Want to drink a kaffee go with me? . |
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``` |
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