Instructions to use buddhilive/bert-base-zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use buddhilive/bert-base-zero with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="buddhilive/bert-base-zero")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("buddhilive/bert-base-zero") model = AutoModelForMaskedLM.from_pretrained("buddhilive/bert-base-zero") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce02e0d8e4cee6cc1d24f056bc178451797597ff89348d608119662a137e62e7
- Size of remote file:
- 655 MB
- SHA256:
- de750da2c61c0f3700081c9b2cfdbcd74ce7bb445f346161b3bb9ee1da407eef
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