Instructions to use Helsinki-NLP/opus-mt-xh-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-xh-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-xh-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-xh-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-xh-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ac88e9fd10736e3d0812e75447c4c6479ad0148399e5ef4237896fa087462ce
- Size of remote file:
- 305 MB
- SHA256:
- d75218c5d0629b389e27b9499eb11aa3e584b8e94055ecac576ddfcc31ec47ad
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