Instructions to use srcocotero/bert-qa-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srcocotero/bert-qa-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="srcocotero/bert-qa-en")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srcocotero/bert-qa-en") model = AutoModelForQuestionAnswering.from_pretrained("srcocotero/bert-qa-en") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on the plain_text config and validation split of squad
#1
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 plain_text config and validation split of the squad dataset by @abrar06 , 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.