Instructions to use DunnBC22/bert-base-uncased-Q_and_A-Answer_Prediction_Dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/bert-base-uncased-Q_and_A-Answer_Prediction_Dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="DunnBC22/bert-base-uncased-Q_and_A-Answer_Prediction_Dataset")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("DunnBC22/bert-base-uncased-Q_and_A-Answer_Prediction_Dataset") model = AutoModelForQuestionAnswering.from_pretrained("DunnBC22/bert-base-uncased-Q_and_A-Answer_Prediction_Dataset") - 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