Instructions to use Helsinki-NLP/opus-mt-es-eo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-eo 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-eo")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-eo") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-eo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 049fb2519659364517000917123d9692bb1a6defe96d173e70bdaf90f240a6b4
- Size of remote file:
- 298 MB
- SHA256:
- 8722b483ae5ec5e534b4c944ffbc02d5d1ff77f08b4990d766af4543e15036d6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.