Instructions to use btk-mufi/bert-pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use btk-mufi/bert-pretrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="btk-mufi/bert-pretrain", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("btk-mufi/bert-pretrain") model = AutoModelForMaskedLM.from_pretrained("btk-mufi/bert-pretrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d0404a1fd69ebb02a4f57dac6cec732f1abb0b8865ff475a5ae32d1c677fcbc
- Size of remote file:
- 436 MB
- SHA256:
- c58a6ef19d24c1ecd6b7fb11104d9e53084a52c6b40e29dcc62f792b1f0b1b90
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