Translation
Transformers
PyTorch
TensorBoard
English
Chinese
marian
text2text-generation
Generated from Trainer
Instructions to use DunnBC22/opus-mt-zh-en-Chinese_to_English with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/opus-mt-zh-en-Chinese_to_English 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="DunnBC22/opus-mt-zh-en-Chinese_to_English")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DunnBC22/opus-mt-zh-en-Chinese_to_English") model = AutoModelForSeq2SeqLM.from_pretrained("DunnBC22/opus-mt-zh-en-Chinese_to_English") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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license:
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base_model: Helsinki-NLP/opus-mt-zh-en
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tags:
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- generated_from_trainer
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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license: apache-2.0
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base_model: Helsinki-NLP/opus-mt-zh-en
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tags:
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- generated_from_trainer
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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## License Notice
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This model is a fine-tuned derivative of a pretrained model.
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Users must comply with the original model license.
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## Dataset Notice
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This model was fine-tuned on third-party datasets which may have separate licenses or usage restrictions.
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