Instructions to use Helsinki-NLP/opus-mt-zh-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-zh-en 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-zh-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-zh-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-zh-en") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b77fd6a4b35423582d47b1de30a6bd174c059a61d6a9b36e260b26e9adbf0b33
- Size of remote file:
- 313 MB
- SHA256:
- 5cfa433c98aeeaa39d7e93f317787467ecb9696b440b96e6d6a4ae3a91b2fb99
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