nvidia
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nemotron-graphic-elements-v1

@@ -29,10 +29,11 @@ The **NeMo Retriever Graphic Elements v1** model is a specialized object detecti
 The model excels at detecting and localizing various graphic elements within chart images, including titles, axis labels, legends, and data point annotations. This capability makes it particularly valuable for document understanding tasks and automated data extraction from visual content.
-This model is ready for commercial use and is a part of the NVIDIA NeMo Retriever family of NIM microservices specifically for object detection and multimodal extraction of enterprise documents.
 This model supersedes the [CACHED](https://build.nvidia.com/university-at-buffalo/cached) model.
 ### License/Terms of use
 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/) and the use of the post-processing scripts are licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt).
@@ -302,7 +303,7 @@ NVIDIA believes Trustworthy AI is a shared responsibility and we have establishe
 | Verified to have met prescribed NVIDIA quality standards: | Yes |
 | Performance Metrics: | Mean Average Precision, detectionr recall and visual inspection |
 | Potential Known Risks: | This model may not always detect all elements in a document. |
-| 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://www.apache.org/licenses/LICENSE-2.0.txt). |
 ## Privacy

 The model excels at detecting and localizing various graphic elements within chart images, including titles, axis labels, legends, and data point annotations. This capability makes it particularly valuable for document understanding tasks and automated data extraction from visual content.
+This model is ready for commercial use and is a part of the NVIDIA NeMo Retriever family of NIM microservices specifically for object detection and multimodal extraction of enterprise documents. For users interested in deploying this model in production environments, it is also available via the model API in NVIDIA Inference Microservices (NIM) at [nemoretriever-graphic-elements-v1](https://build.nvidia.com/nvidia/nemoretriever-graphic-elements-v1).
 This model supersedes the [CACHED](https://build.nvidia.com/university-at-buffalo/cached) model.
 ### License/Terms of use
 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/) and the use of the post-processing scripts are licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt).
 | Verified to have met prescribed NVIDIA quality standards: | Yes |
 | Performance Metrics: | Mean Average Precision, detectionr recall and visual inspection |
 | Potential Known Risks: | This model may not always detect all elements in a document. |
+| Licensing & Terms of Use: | 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/) and the use of the post-processing scripts are licensed under [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt). |
 ## Privacy