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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#4 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#3 opened over 3 years ago
by
SFconvertbot
Add evaluation results on the autoevaluate--squad-sample config and test split of autoevaluate/squad-sample
#2 opened over 3 years ago
by
autoevaluator
Add evaluation results on the autoevaluate--squad-sample config and test split of autoevaluate/squad-sample
#1 opened over 3 years ago
by
lewtun