From 41a8adce1a67ded9a85d11a040034992334e3985 Mon Sep 17 00:00:00 2001 From: Sierra Guequierre Date: Thu, 12 Dec 2024 15:54:56 -0500 Subject: [PATCH] update table --- docs/data-ai/ai/deploy.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/data-ai/ai/deploy.md b/docs/data-ai/ai/deploy.md index e4b091b2e8..919e610b3d 100644 --- a/docs/data-ai/ai/deploy.md +++ b/docs/data-ai/ai/deploy.md @@ -28,12 +28,12 @@ Add an ML model service that supports the ML model you trained or the one you wa Viam currently supports the following frameworks: -| Model Framework | ML Model Service | Hardware Support | System Architecture | Description | -| --------------- | --------------- | ---------------- | ------------------- | ----------- | -| [TensorFlow Lite](https://www.tensorflow.org/lite) | [`tflite_cpu`](https://github.com/viam-modules/mlmodel-tflite) | Any CPU
Nvidia GPU | Linux, Raspbian, MacOS | Quantized version of TensorFlow that has reduced compatibility for models but supports more hardware. Uploaded models must adhere to the [model requirements.](https://github.com/viam-modules/mlmodel-tflite) | -| [ONNX](https://onnx.ai/) | [`onnx-cpu`](https://github.com/viam-labs/onnx-cpu) | Any CPU
Nvidia GPU | Android, MacOS, Linux arm-64 | Universal format that is not optimized for hardware inference but runs on a wide variety of machines. | -| [TensorFlow](https://www.tensorflow.org/) | [`tensorflow-cpu`](https://github.com/viam-modules/tensorflow-cpu), [`triton`](https://github.com/viamrobotics/viam-mlmodelservice-triton) | Any CPU
Nvidia GPU | Linux, Raspbian, MacOS | A full framework that is made for more production-ready systems. | -| [PyTorch](https://pytorch.org/) | [`torch-cpu`](https://github.com/viam-modules/torch), [`triton`](https://github.com/viamrobotics/viam-mlmodelservice-triton) | Any CPU
Nvidia GPU | Linux, Raspbian, MacOS | A full framework that was built primarily for research. Because of this, it is much faster to do iterative development with (model doesn’t have to be predefined) but it is not as “production ready” as TensorFlow. It is the most common framework for OSS models because it is the go-to framework for ML researchers. | +| Model Framework | ML Model Service | Hardware Support | Description | +| --------------- | --------------- | ------------------- | ----------- | +| [TensorFlow Lite](https://www.tensorflow.org/lite) | [`tflite_cpu`](https://github.com/viam-modules/mlmodel-tflite) | linux/amd64, linux/arm64, darwin/arm64, darwin/amd64 | Quantized version of TensorFlow that has reduced compatibility for models but supports more hardware. Uploaded models must adhere to the [model requirements.](https://github.com/viam-modules/mlmodel-tflite) | +| [ONNX](https://onnx.ai/) | [`onnx-cpu`](https://github.com/viam-labs/onnx-cpu), [`triton`](https://github.com/viamrobotics/viam-mlmodelservice-triton) | Nvidia GPU, linux/amd64, linux/arm64, darwin/arm64 | Universal format that is not optimized for hardware inference but runs on a wide variety of machines. | +| [TensorFlow](https://www.tensorflow.org/) | [`tensorflow-cpu`](https://github.com/viam-modules/tensorflow-cpu), [`triton`](https://github.com/viamrobotics/viam-mlmodelservice-triton) | Nvidia GPU, linux/amd64, linux/arm64, darwin/arm64 | A full framework that is made for more production-ready systems. | +| [PyTorch](https://pytorch.org/) | [`torch-cpu`](https://github.com/viam-modules/torch), [`triton`](https://github.com/viamrobotics/viam-mlmodelservice-triton) | Nvidia GPU, linux/arm64, darwin/arm64 | A full framework that was built primarily for research. Because of this, it is much faster to do iterative development with (model doesn’t have to be predefined) but it is not as “production ready” as TensorFlow. It is the most common framework for OSS models because it is the go-to framework for ML researchers. | {{< alert title="Note" color="note" >}} For some models of the ML model service, like the [Triton ML model service](https://github.com/viamrobotics/viam-mlmodelservice-triton/) for Jetson boards, you can configure the service to use either the available CPU or a dedicated GPU.