Instructions to use nghuyong/ernie-2.0-base-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nghuyong/ernie-2.0-base-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nghuyong/ernie-2.0-base-en")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nghuyong/ernie-2.0-base-en") model = AutoModel.from_pretrained("nghuyong/ernie-2.0-base-en") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:af27705a979a8c5ad867fca358b911297a823def39a2727dd7c7aaa855cdd49e
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size 440474579
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