Instructions to use Helsinki-NLP/opus-mt-en-phi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-phi 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-phi")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-phi") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-phi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f53cd7c06fd77f4a42c9aa9309ab78c409d115fece77ce2cd5df23714efbd96b
- Size of remote file:
- 302 MB
- SHA256:
- a6ad3c7c25aa6605911161f533e372bcd1de43b8d40600340200d91e0c2157e2
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