Instructions to use magicslabnu/BERT_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use magicslabnu/BERT_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="magicslabnu/BERT_base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("magicslabnu/BERT_base") model = AutoModelForMaskedLM.from_pretrained("magicslabnu/BERT_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e3265d2136f12ebcca88f17622bdebcaa28c7093c26729080259cd8bd9d264d
- Size of remote file:
- 438 MB
- SHA256:
- 7d9116f48f278649299832c6b5808f15cb55aee2db3b0125afb6bbf43167a59e
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