Instructions to use deepset/bert-base-uncased-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/bert-base-uncased-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/bert-base-uncased-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/bert-base-uncased-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/bert-base-uncased-squad2") - Inference
- Notebooks
- Google Colab
- Kaggle
Add evaluation results on the adversarialQA config of adversarial_qa
#2
by autoevaluator HF Staff - opened
README.md
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@@ -23,6 +23,23 @@ model-index:
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type: f1
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value: 78.6191
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verified: true
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---
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# bert-base-uncased for QA
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type: f1
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value: 78.6191
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verified: true
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: adversarial_qa
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type: adversarial_qa
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config: adversarialQA
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split: validation
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metrics:
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- name: Exact Match
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type: exact_match
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value: 23.1333
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verified: true
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- name: F1
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type: f1
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value: 34.5358
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verified: true
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---
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# bert-base-uncased for QA
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