Question Answering
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use mrp/bert-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrp/bert-finetuned-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrp/bert-finetuned-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrp/bert-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("mrp/bert-finetuned-squad") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on the adversarialQA config and validation split of adversarial_qa
#3
by autoevaluator HF Staff - opened
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!
Your model has been evaluated on the adversarialQA config and validation split of the adversarial_qa dataset by @mbartolo , using the predictions stored here.
Accept this pull request to see the results displayed on the Hub leaderboard.
Evaluate your model on more datasets here.