Instructions to use google-bert/bert-large-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-large-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-large-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-large-uncased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-large-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f674bb0eb4a3ec5b05a350ca502bea12360c19d2ea3bea93eccc1c105cd24a45
- Size of remote file:
- 1.34 GB
- SHA256:
- be24b235c46198938ac269939f8341ae479f2150dc278a342a3ffddefad35434
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