Instructions to use Helsinki-NLP/opus-mt-en-bi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-bi 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-bi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-bi") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-bi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c2df55693be8129a6b96a971c6da4964bed9c952174c9b407ca0702e8ebf7be
- Size of remote file:
- 290 MB
- SHA256:
- 30b8d3a7bac0bc20c2a2b564e3715d46103563fe284a4d9cc4769cf07086a4ea
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