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
Librarian Bot: Add base_model information to model
#3 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#2 opened almost 3 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot