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:
- db34bac9beae86f7a6c6fe488caecd6f788acc608c7598cae2cb0e023ff25e50
- Size of remote file:
- 290 MB
- SHA256:
- 6a018727d1e79a53390c124ec20b976a2c0ef3711c505966d83c86a4841ee7b9
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