lysandre HF staff commited on
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Update dimensions

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  1. README.md +7 -0
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@@ -41,6 +41,13 @@ This way, the model learns an inner representation of the English language that
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  useful for downstream tasks: if you have a dataset of labeled sentences for instance, you can train a standard
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  classifier using the features produced by the BERT model as inputs.
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  ## Intended uses & limitations
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  This model should be used as a question-answering model. You may use it in a question answering pipeline, or use it to output raw results given a query and a context. You may see other use cases in the [task summary](https://huggingface.co/transformers/task_summary.html#extractive-question-answering) of the transformers documentation.## Training data
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  useful for downstream tasks: if you have a dataset of labeled sentences for instance, you can train a standard
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  classifier using the features produced by the BERT model as inputs.
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+ This model has the following configuration:
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+
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+ - 24-layer
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+ - 1024 hidden dimension
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+ - 16 attention heads
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+ - 336M parameters.
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+
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  ## Intended uses & limitations
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  This model should be used as a question-answering model. You may use it in a question answering pipeline, or use it to output raw results given a query and a context. You may see other use cases in the [task summary](https://huggingface.co/transformers/task_summary.html#extractive-question-answering) of the transformers documentation.## Training data
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