Instructions to use VMware/bert-base-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/bert-base-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/bert-base-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/bert-base-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/bert-base-mrqa") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -46,7 +46,12 @@ result = question_answerer(question=question, context=context)
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print(result)
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# {
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```
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print(result)
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# {
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# 'score': 0.9254004955291748,
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# 'start': 30,
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# 'end': 68,
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# 'answer': 'Machine Reading for Question Answering'
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# }
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```
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