Instructions to use Helsinki-NLP/opus-mt-ve-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-ve-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-ve-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ve-es") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ve-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a57a31b42a86ca44fe6c0bfed5342638533569e8b29ba5393d008a05e5dde0bd
- Size of remote file:
- 294 MB
- SHA256:
- 470b86313eb4ffa62caf455f9d3602e63e22178610475d7647321ffa0ac08dbe
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