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
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:eed8ca081a8a6bd3e5b79291417695092a28ef2e1a1a21ddd81dafe060005bb2
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size 438085080
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