Instructions to use Helsinki-NLP/opus-mt-en-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-en-zh 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-zh")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-zh") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-zh") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e06e5fab70bfb258347407cca44031ec4f210f2bcade8ffa03424f0e61b7fc7
- Size of remote file:
- 312 MB
- SHA256:
- 69a1d6ec829cee349360b3b677ac0aa99a7d88822d1a6578370029efffdca3f5
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