Instructions to use Helsinki-NLP/opus-mt-es-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-mt 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-mt")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-mt") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-mt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 223b294b82a9c331277ca3690202b35dd0410263003f6e8b731c81837a887644
- Size of remote file:
- 296 MB
- SHA256:
- b30cabea84420e82171bf8d461150ae2cc24ab3e255814fbbbc3150ca882e167
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