Instructions to use dewdev/question_and_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dewdev/question_and_answer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="dewdev/question_and_answer")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("dewdev/question_and_answer") model = AutoModelForQuestionAnswering.from_pretrained("dewdev/question_and_answer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| license: apache-2.0 | |
| base_model: distilbert/distilbert-base-cased-distilled-squad | |
| tags: | |
| - generated_from_keras_callback | |
| model-index: | |
| - name: Docty/question_and_answer | |
| results: [] | |
| this is a clone of Docty/question_and_answer | |