Instructions to use Helsinki-NLP/opus-mt-es-tzo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-tzo 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-tzo")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-tzo") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-tzo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d9a2604b18c58b089ded3bb6831e338ff0410a2ca78889469ace40c8b978b21
- Size of remote file:
- 290 MB
- SHA256:
- f9bbd79f993e9c73263d814c534dadb91338e7188b0a436eeb8de3786caa125a
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