Instructions to use Helsinki-NLP/opus-mt-af-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-af-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-af-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-af-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-af-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df4dfe55b1ad1554601c5a03e6a00ea44d62608735f1002c7fe115ffa29b1f35
- Size of remote file:
- 302 MB
- SHA256:
- 7402441ff99044efa698bb20ca94103aa9d58e2f2c9d58a45ec4f451f1020eb9
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