Instructions to use Helsinki-NLP/opus-mt-pap-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-pap-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-pap-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-pap-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-pap-es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bc7427ec584f06ae50cee5e73843aa4bac8f774f1b9fc86358442f696abb3ca
- Size of remote file:
- 294 MB
- SHA256:
- 14ed68bc1a10296b30985c676fd1ed92154704f994c093f4d3c36e97676736a6
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