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:
- 83466f2ffeab8a5cb7c674ae0fb7631bfaae42478ab0db5e553bd78984f7b04f
- Size of remote file:
- 438 MB
- SHA256:
- 7becd045c514f4bf7e570adfdae512dc826833db926a4317fec81146054494c6
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