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@@ -88,6 +88,10 @@ These examples, along with our NVIDIA deep learning software stack, are provided
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| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
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| [SE(3)-Transformer](https://github.com/NVIDIA/DeepLearningExamples/tree/master/DGLPyTorch/DrugDiscovery/SE3Transformer) | PyTorch | Yes | Yes | Yes | - | - | - | - | - | - |
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+## Time-Series Forecasting
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+| Models | Framework | A100 | AMP | Multi-GPU | Multi-Node | TRT | ONNX | Triton | DLC | NB |
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+| ------------- | ------------- | ------------- | ------------- | ------------- | ------------- |------------- |------------- |------------- |------------- |------------- |
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+| [Temporal Fusion Transformer](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Forecasting/TFT) | PyTorch | Yes | Yes | Yes | - | Yes | Yes | [Yes](https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch/Forecasting/TFT/triton) | Yes | - |
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## NVIDIA support
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In each of the network READMEs, we indicate the level of support that will be provided. The range is from ongoing updates and improvements to a point-in-time release for thought leadership.
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Izzy Putterman