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
- Xet hash:
- 87f7ae9e8eca0206f3abfa8e1a67c1712ef606188d992de08884339088d711a0
- Size of remote file:
- 438 MB
- SHA256:
- 1554b651032ce896c15acf6551496fc9e3c7aa16ac5c8b1a2b499b964f49fb8d
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