Model Card for Model ID
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Model Details
Model Description
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Uses
import ctranslate2
import transformers
translator = ctranslate2.Translator("t5_ct2")
tokenizer = transformers.AutoTokenizer.from_pretrained("t5_ct2")
input_text = " translate German to English: Ich erkläre die am Freitag, dem 17. Dezember 1999 unterbrochene Sitzungsperiode des Europäischen Parlaments für wieder aufgenommen, und wünsche Ihnen nochmals ein glückliches neues Jahr in der Hoffnung, daß Sie eine angenehme Festzeit genossen haben. Obwohl der gefürchtete 'Jahrtausendfehler' nicht zustande gekommen ist, erlitten die Menschen in einigen Ländern noch immer eine Reihe von Naturkatastrophen, die wirklich furchtbar waren."
input_tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(input_text))
results = translator.translate_batch([input_tokens])
output_tokens = results[0].hypotheses[0]
output_text = tokenizer.decode(tokenizer.convert_tokens_to_ids(output_tokens))
print(output_text)
If u want to translate en to de , you can change the prefix " translate English to German" is ok.
Direct Use
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Out-of-Scope Use
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
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Training Details
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Training Procedure
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Evaluation
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Summary
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Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
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