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Sahajtomar
/
GBERTQnA

Question Answering Transformers PyTorch TensorFlow JAX
German bert Inference Endpoints
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@@ -45,7 +45,7 @@ qa_pipeline({
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  # output
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- {'answer': 'APOBEC', 'end': 121, 'score': 0.9795194864273071, 'start': 115}
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  ## Even complex queries can be answered pretty well
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@@ -65,4 +65,4 @@ qa_pipeline({
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  Try it on a Colab:
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- <a href="https://github.com/Sahajtomar/Question-Answering/blob/main/Sahajtomar_GBERTQA.ipynb" target="_parent"><img src="https://camo.githubusercontent.com/52feade06f2fecbf006889a904d221e6a730c194/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Open In Colab" data-canonical-src="https://colab.research.google.com/assets/colab-badge.svg"></a>
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  # output
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+ {'answer': 'APOBEC', 'end': 121, 'score': 0.9815779328346252, 'start': 115}
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  ## Even complex queries can be answered pretty well
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  Try it on a Colab:
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+ <a href="https://github.com/Sahajtomar/Question-Answering/blob/main/Sahajtomar_GBERTQnA.ipynb" target="_parent"><img src="https://camo.githubusercontent.com/52feade06f2fecbf006889a904d221e6a730c194/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Open In Colab" data-canonical-src="https://colab.research.google.com/assets/colab-badge.svg"></a>