Instructions to use Helsinki-NLP/opus-mt-ar-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-ar-es 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="Helsinki-NLP/opus-mt-ar-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ar-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ar-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7759b3ec7bc1f291bfaaf57f1894a08498eda5b201dfb1b821391dbe9c7a217
- Size of remote file:
- 307 MB
- SHA256:
- ef46ef6938da0a28f88a5348516e3fbb096923e9ef272d8789ce6cdbd0c5755a
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