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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adds tokenizer_config.json file
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addition of Rust model (#2)
Verified signature- addition of Rust model (cf3f2250613a124f105776a20f769b8120ab617b) Co-authored-by: Kavan Mevada <kavanmevada@users.noreply.huggingface.co>3c3da4a
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (0336813fa3333c168229e8389d0d3bfe8cefa08f) Co-authored-by: Nicolas Patry <Narsil@users.noreply.huggingface.co>80792f8
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For clarity, delete deprecated modelcard.json
We now use the README.md model card instead Approved-by: Julien Chaumond <julien@huggingface.co>0ce9a5b
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Add tokenizer configuration
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