Instructions to use google/bert2bert_L-24_wmt_en_de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/bert2bert_L-24_wmt_en_de with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="google/bert2bert_L-24_wmt_en_de")# Load model directly 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") - Notebooks
- Google Colab
- Kaggle
Add multilingual to the language tag
#1
by lbourdois - opened
README.md
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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_en_de EncoderDecoder model
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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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#
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---
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language:
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- en
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- de
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- multilingual
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license: apache-2.0
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tags:
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- translation
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datasets:
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- wmt14
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---
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# bert2bert_L-24_wmt_en_de EncoderDecoder model
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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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# M�chten Sie diese Woche einen Kaffee mit mir schnappen?
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