Instructions to use Falconsai/question_answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/question_answering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Falconsai/question_answering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Falconsai/question_answering") model = AutoModelForQuestionAnswering.from_pretrained("Falconsai/question_answering") - Notebooks
- Google Colab
- Kaggle
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# Model Card: Fine-tuned DistilBERT-base-uncased for Question and Answering
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widget:
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- text: "What's my name?"
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context: "My name is Soren and I live in the Hills."
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example_title: "Name"
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- text: "Where do I live?"
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context: "My name is Shannon and I live in Macon"
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example_title: "Location"
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# Model Card: Fine-tuned DistilBERT-base-uncased for Question and Answering
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