Instructions to use DunnBC22/bert-base-uncased-Masked_Language_Modeling-AG_News with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/bert-base-uncased-Masked_Language_Modeling-AG_News with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DunnBC22/bert-base-uncased-Masked_Language_Modeling-AG_News")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DunnBC22/bert-base-uncased-Masked_Language_Modeling-AG_News") model = AutoModelForMaskedLM.from_pretrained("DunnBC22/bert-base-uncased-Masked_Language_Modeling-AG_News") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85e2eded86973a05bccc8aefa883a09e6603ee5c35be8d7edb11d44e653fd3a7
- Size of remote file:
- 3.52 kB
- SHA256:
- df078ac209e70d345dfb6c6678389d8683d0e819ec35286e9999749a0a2a9526
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