Instructions to use google-bert/bert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-cased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69303f891258871478549f52770b52f00b0c8a67053c57e06631f8973786718c
- Size of remote file:
- 433 MB
- SHA256:
- 2da0d47987f1ad37febaaa06c3bec9134c1b1d3a6ebf134af5f946ce8aeaf630
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