Translation
Transformers
PyTorch
TensorFlow
Spanish
Mexican Sign Language
marian
text2text-generation
Instructions to use Helsinki-NLP/opus-mt-es-mfs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-mfs 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-es-mfs")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-mfs") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-mfs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 877ee2e2b7c5d87fd63d2dc33123ea0242ce290de1db2c474d82d2f0e1478781
- Size of remote file:
- 237 MB
- SHA256:
- 5f85e71f832a44bc049714aa982422ed826d1c90262d1ce6375e1b8c3be114cc
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