Instructions to use google-bert/bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33ffdfe1fe90b9aaa2e79168c0141c72645c865bf1990b7a0975929862c34b45
- Size of remote file:
- 534 MB
- SHA256:
- afd9aa425fd45c5655d3d43a0d041f9b76729bf475d6c017a0e9304a38f89972
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