Instructions to use Helsinki-NLP/opus-mt-es-tpi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-es-tpi 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-tpi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-es-tpi") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-es-tpi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75b7e9c97c9cd2f9174c61d80dbb50e8dff6ed7717bf8aea13a880bb84a3d4bd
- Size of remote file:
- 287 MB
- SHA256:
- 600ff0689602088c047928145d3c41ac281bce648f0e25a908c9d873afd3cd6b
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