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:
- 1dd125a79bf61eb6fcf4ba5f17174c3c7d98f8211d3ad6a5b5a6ad097a2e8f8f
- Size of remote file:
- 304 MB
- SHA256:
- 7e3ba4637b19f5e5d96d403dad6707f4712b7a5b9409c15b9bfee17c57bcafbc
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