nodes/city96-SD-Latent-Interposer
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Option to directly clone the repo to custom_nodes

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City
2023-08-08 12:19:39 +02:00
parent bfa760107f
commit a76f5c8555
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README.md
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@@ -4,7 +4,9 @@ A small neural network to provide interoperability between the latents generated
I wanted to see if it was possible to pass latents generated by the new SDXL model directly into SDv1.5 models without decoding and re-encoding them using a VAE first. I wanted to see if it was possible to pass latents generated by the new SDXL model directly into SDv1.5 models without decoding and re-encoding them using a VAE first.
## Installation ## Installation
To install it, simply download [comfy_latent_interposer.py](https://github.com/city96/SD-Latent-Interposer/raw/main/comfy_latent_interposer.py) to your `ComfyUI/custom_nodes` folder. You may need to install hfhub using the command `pip install huggingface-hub` inside your venv. To install it, simply clone this repo to your custom_nodes folder using the following command: `git clone https://github.com/city96/SD-Latent-Interposer custom_nodes/SD-Latent-Interposer`.
Alternatively, you can download the [comfy_latent_interposer.py](https://github.com/city96/SD-Latent-Interposer/raw/main/comfy_latent_interposer.py) file to your `ComfyUI/custom_nodes` folder as well. You may need to install hfhub using the command `pip install huggingface-hub` inside your venv.
If you need the model weights for something else, they are [hosted on HF](https://huggingface.co/city96/SD-Latent-Interposer/tree/main) under the same Apache2 license as the rest of the repo. If you need the model weights for something else, they are [hosted on HF](https://huggingface.co/city96/SD-Latent-Interposer/tree/main) under the same Apache2 license as the rest of the repo.
__init__.py
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# only import if running as a custom node
try:
import comfy.utils
except ImportError:
pass
else:
from .comfy_latent_interposer import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']