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Content Type Classifier #361
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Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
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Mostly looks good, minor feedback
Signed-off-by: Sarah Yurick <[email protected]>
Signed-off-by: Sarah Yurick <[email protected]>
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LGTM
ContentTypeClassifier is a text classification model designed to categorize documents into one of 11 distinct speech types based on their content. | ||
It analyzes and understands the nuances of textual information, enabling accurate classification across a diverse range of content types. | ||
The pretrained model used by this class can be found on Hugging Face here: https://huggingface.co/nvidia/content-type-classifier-deberta. | ||
This class is optimized for running on multi-node, multi-GPU setups to enable fast and efficient inference on large datasets. |
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This class is optimized for running on multi-node, multi-GPU setups to enable fast and efficient inference on large datasets. | |
This classifier is optimized for running on multi-node, multi-GPU setups to enable fast and efficient inference on large datasets. |
Signed-off-by: Sarah Yurick <[email protected]>
Awaiting Hugging Face release: https://huggingface.co/nvidia/content-type-classifier-deberta.