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:
- 308798ea9e5033f9e36c1f524f1675d6495abc119f603157d28b049066968043
- Size of remote file:
- 876 MB
- SHA256:
- 4ca6993deac3588e1ea30f8876534a843ef79c240775eec08d069d8b9225fb55
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