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Update UNCLIP.MD

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@ -5,14 +5,16 @@ trained to invert CLIP image embeddings.
We finetuned SD 2.1 to accept a CLIP ViT-L/14 image embedding in addition to the text encodings.
This means that the model can be used to produce image variations, but can also be combined with a text-to-image
embedding prior to yield a full text-to-image model at 768x768 resolution.
If you would like to try a demo of this model on the web, please visit https://clipdrop.co/stable-diffusion-reimagine
We provide two models, trained on OpenAI CLIP-L and OpenCLIP-H image embeddings, respectively,
available from [https://huggingface.co/stabilityai/stable-diffusion-2-1-unclip](https://huggingface.co/stabilityai/stable-diffusion-2-1-unclip/tree/main).
To use them, download from Hugging Face, and put and the weights into the `checkpoints` folder.
To use them, download from Hugging Face, and put and the weights into the `checkpoints` folder.
#### Image Variations
![image-variations-l-1](../assets/stable-samples/stable-unclip/unclip-variations.png)
If you would like to try a demo of this model, please visit https://clipdrop.co/stable-diffusion-reimagine
Run
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