Instructions to use Helsinki-NLP/opus-mt-en-ty with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-ty 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-en-ty")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ty") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-ty") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c495af0a574c71525107f523f7786aec91d5495d24ba385c83e17f7349ae069
- Size of remote file:
- 295 MB
- SHA256:
- 0739c07656407aff573e4a14195b8bfc69688c5b0454ee28ec559885e0679335
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