nvidia
/

domain-classifier

pytorch_model_hub_mixin

model_hub_mixin

Inference Endpoints

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ryantwolf commited on Jun 24

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@@ -40,7 +40,7 @@ Food_and_Drink
 # How to use in NeMo Curator
-The inference code is available on NeMo Curator's GitHub repository. Download the [model.pth](https://huggingface.co/nvidia/domain-classifier/blob/main/model.pth) file and check out this [example notebook](https://github.com/NVIDIA/NeMo-Curator/blob/main/tutorials/distributed_data_classification/distributed_data_classification.ipynb) to get started.
 # How to use in transformers
 To use the Domain classifier, use the following code:
@@ -90,7 +90,7 @@ PR-AUC score on evaluation set with 105k samples - 0.9873
 PR-AUC score for each domain:
 | Domain                   | PR-AUC |
-|--------------------------|--------|
 | Adult                    | 0.999  |
 | Arts_and_Entertainment   | 0.997  |
 | Autos_and_Vehicles       | 0.997  |

 # How to use in NeMo Curator
+The inference code is available on [NeMo Curator's GitHub repository](https://github.com/NVIDIA/NeMo-Curator). Download the [model.pth](https://huggingface.co/nvidia/domain-classifier/blob/main/model.pth) file and check out this [example notebook](https://github.com/NVIDIA/NeMo-Curator/blob/main/tutorials/distributed_data_classification/distributed_data_classification.ipynb) to get started.
 # How to use in transformers
 To use the Domain classifier, use the following code:
 PR-AUC score for each domain:
 | Domain                   | PR-AUC |
+|:-------------------------|:-------|
 | Adult                    | 0.999  |
 | Arts_and_Entertainment   | 0.997  |
 | Autos_and_Vehicles       | 0.997  |