Instructions to use Helsinki-NLP/opus-mt-en-pqe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-pqe 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-pqe")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-pqe") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-pqe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 394ef086ab9134aab8c81439e448d86fb11c028a9feac72c619ef6f798d29bc1
- Size of remote file:
- 302 MB
- SHA256:
- 3b79faa34999910f1c6db2c0c4dbda0e0a9208a8e08c1ab666b101794812d6a0
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