# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Tanhim/translation-En2De")
model = AutoModelForSeq2SeqLM.from_pretrained("Tanhim/translation-En2De")Quick Links
English to German Translation
Model Name: Tanhim/translation-En2De
language: German or Deutsch
thumbnail: https://huggingface.co/Tanhim/translation-En2De
How to use
You can use this model directly with a pipeline for machine translation. Since the generation relies on some randomness, I set a seed for reproducibility:
>>> from transformers import pipeline, set_seed
>>> text_En2De= pipeline('translation', model='Tanhim/translation-En2De', tokenizer='Tanhim/translation-En2De')
>>> set_seed(42)
>>> text_En2De("My name is Karl and I live in Aachen")
beta version
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# 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="Tanhim/translation-En2De")