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README.md
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widget:
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- text: My name is Maria
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tags:
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- translation
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license: gpl
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---
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widget:
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- text: My name is Maria
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tags:
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- translation
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datasets:
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- wmt19
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license: gpl
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---
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<h2> English to German Translation </h2>
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Model Name: Tanhim/translation-En2De <br />
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language: German or Deutsch <br />
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thumbnail: https://huggingface.co/Tanhim/translation-En2De <br />
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### How to use
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You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, I
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set a seed for reproducibility:
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```python
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>>> from transformers import pipeline, set_seed
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>>> text_En2De= pipeline('translation', model='Tanhim/translation-En2De', tokenizer='Tanhim/translation-En2De')
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>>> set_seed(42)
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>>> text_En2De("My name is Maria,")
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```
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#Beta version
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