Instructions to use Helsinki-NLP/opus-mt-es-et with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-et 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-et")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-et") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-et", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c7896e35c5088117d9ba9162073a9c488e65d75b800f3f798cf27806db122b1
- Size of remote file:
- 298 MB
- SHA256:
- 69959909c9e0e259d8e273f589b6a8bd734d0d5af2fb5ae3e6b9081a0c6f17fe
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