Translation
Transformers
PyTorch
TensorFlow
Mexican Sign Language
Spanish
marian
text2text-generation
Instructions to use Helsinki-NLP/opus-mt-mfs-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-mfs-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-mfs-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-mfs-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-mfs-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaaaad520eed8c86f405571c98fdb399a2f6e8832973d5264eda27e27c5bc6a6
- Size of remote file:
- 237 MB
- SHA256:
- 45eedcf4ab625ad583ac9471ed93c892157f787af8f2aa53ac013b61eff3dfc4
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