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@@ -244,5 +244,19 @@ down-scaled or abstract images work great but this only plays a small role in th
### System Requirements
Works out-of-the-box on CPU via `onnxruntime`. For **10×** speed improvement ensure ComfyUI can use the `CUDAExecutionProvider` by using onnxruntime-gpu with the hardware that allows this.
This node print out the currently available providers into the ComfyUI server logs if you need to check this.
Works out-of-the-box on CPU via `onnxruntime` but it is extremely slow. For **10×** speed improvement ensure ComfyUI can use the `CUDAExecutionProvider` by installing `onnxruntime-gpu` into the ComfyUI environment.
This node currently prints out the available providers for onnxruntime into the ComfyUI server logs when you run the node. So if you are not seeing `CUDAExecutionProvider` it's likely the model is using CPU instead.
For reference I use:
Python version: 3.12.1
pytorch version: 2.5.0+cu124
NVIDIA GeForce RTX 4090
Results - Server Logs show:
[SuperBeasts] ONNX Runtime providers available: ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider']
[SuperBeasts] Using ORT providers: ['CUDAExecutionProvider', 'CPUExecutionProvider']
1024x1024px with 0.5 overlap = 1.63s
2048x2048px with 0.5 overlap = 5.23s
Note: I am aware the extra installation of `onnxruntime-gpu` isn't ideal and I'm attempting to convert the model into .safetensors to work within the ComfyUI Pytorch environment better with less issues accessing the GPU.