Instructions to use Helsinki-NLP/opus-mt-bem-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-bem-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-bem-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-bem-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-bem-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6eaea049833af3cb74238aabe174dc10793d2290c65f37f48d686e1fae82d73e
- Size of remote file:
- 304 MB
- SHA256:
- 1ec9b23bc9125c979f9bf93124b41a2ba1af3264e271501887fb8e3fd3ebb307
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