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@@ -35,7 +35,7 @@ This model supersedes the [CACHED](https://build.nvidia.com/university-at-buffal
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  ### License/Terms of use
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- The use of this model is governed by the [NVIDIA AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-community-models-license/).
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  **You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.**
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@@ -306,7 +306,7 @@ Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.
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  | Verified to have met prescribed NVIDIA quality standards: | Yes |
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  | Performance Metrics: | Mean Average Precision, detectionr recall and visual inspection |
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  | Potential Known Risks: | This model may not always detect all elements in a document. |
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- | Licensing & Terms of Use: | Use of this model is governed by the [NVIDIA AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-ai-foundation-models-community-license-agreement/) and the [Apache 2.0 License](https://github.com/Megvii-BaseDetection/YOLOX/blob/main/LICENSE). |
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  ## Privacy
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@@ -327,5 +327,5 @@ Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.
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  | ----- | ----- |
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  | Model Application Field(s): | Object Detection for Retrieval, focused on Enterprise |
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  | Describe the life critical impact (if present). | Not Applicable |
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- | Use Case Restrictions: | Abide by [NVIDIA AI Foundation Models Community License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-community-models-license/). |
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  | Model and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to. |
 
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  ### License/Terms of use
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+ The use of this model is governed by the [NVIDIA Open Model License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/).
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  **You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.**
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  | Verified to have met prescribed NVIDIA quality standards: | Yes |
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  | Performance Metrics: | Mean Average Precision, detectionr recall and visual inspection |
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  | Potential Known Risks: | This model may not always detect all elements in a document. |
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+ | Licensing & Terms of Use: | Use of this model is governed by the [NVIDIA Open Model License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/) and the [Apache 2.0 License](https://github.com/Megvii-BaseDetection/YOLOX/blob/main/LICENSE). |
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  ## Privacy
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  | ----- | ----- |
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  | Model Application Field(s): | Object Detection for Retrieval, focused on Enterprise |
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  | Describe the life critical impact (if present). | Not Applicable |
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+ | Use Case Restrictions: | Abide by [NVIDIA Open Model License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/). |
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  | Model and dataset restrictions: | The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to. |