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:
- 879c5715c18a0b7f051dd33f70f0a5c8dd1522e0a43f6f75520f16167f29279b
- Size of remote file:
- 536 MB
- SHA256:
- a7a17d6d844b5de815ccab5f42cad6d24496db3850a2a43d8258221018ce87d2
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