Update README.md

Remove previous instructions for running in ComfyUI. Since Kijai added support for the giant model, no modifications are needed.

README.md

@@ -12,15 +12,19 @@ A copy of the original .pth model is available in this Hugging Face repo: https:
 
 This is simply the same available model in .safetensors format.
 
-If you want to use it in ComfyUI, you have two options:
+If you want to use it in ComfyUI, you can use Kijai's custom nodes (https://github.com/kijai/ComfyUI-DepthAnythingV2), select the model and it will be downloaded automatically.
 
+You may get OOM using the gigant model depending on your VRAM and the size of the image you're processing. In these cases, try to reduce the input image size. I can get 1024x1024 depth maps just fine with 24GB VRAM (uses about 56% of available VRAM).
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+~~If you want to use it in ComfyUI, you have two options:
 
 1. (Recommended) Use the .safetensors file with the modified version of Kijai's custom nodes (https://github.com/kijai/ComfyUI-DepthAnythingV2). Just replace the ComfyUI/custom_nodes/comfyui-depthanythingv2/nodes.py file with the nodes.py file in this repo and ensure depth_anything_v2_vitg_fp32.safetensors is in the ComfyUI/models/depthanything/ folder, as it will not be downloaded automatically.
 
 2. Use depth_anything_v2_vitg.pth directly with Fannovel16's custom nodes (https://github.com/Fannovel16/comfyui_controlnet_aux). Use a node called Depth Anything V2 - Relative and select depth_anything_v2_vitg.pth. Ensure the file is in the folder ComfyUI/custom_nodes/comfyui_controlnet_aux/ckpts/depth-anything/Depth-Anything-V2-Giant/ folder, as it will not be downloaded automatically.
 
 
-Kijai's nodes produce more detailed depth maps. However, you will likely get OOM using the gigant model depending on your VRAM and the size of the image you're processing. I can get 1024x1024 depth maps just fine with 24GB VRAM.
+Kijai's nodes produce more detailed depth maps. However, you will likely get OOM using the gigant model depending on your VRAM and the size of the image you're processing. I can get 1024x1024 depth maps just fine with 24GB VRAM.~~
 
 
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