Instructions to use autoevaluate/extractive-question-answering-not-evaluated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/extractive-question-answering-not-evaluated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="autoevaluate/extractive-question-answering-not-evaluated")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("autoevaluate/extractive-question-answering-not-evaluated") model = AutoModelForQuestionAnswering.from_pretrained("autoevaluate/extractive-question-answering-not-evaluated") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on the autoevaluate--squad-sample config and test split of autoevaluate/squad-sample
#1
by lewtun HF Staff - opened
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!
Your model has been evaluated on the autoevaluate--squad-sample config and test split of the autoevaluate/squad-sample dataset by @lewtun , 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.