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README: stable diffusion version v1-3 -> v1-4 (huggingface#331)
Prose: stable diffusion version v1-3 -> v1-4 The code examples use `v1-4`, but the license text was referring to `v1-3`.
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README.md

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@@ -39,7 +39,7 @@ In order to get started, we recommend taking a look at two notebooks:
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Stable Diffusion is a text-to-image latent diffusion model created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/) and [LAION](https://laion.ai/). It's trained on 512x512 images from a subset of the [LAION-5B](https://laion.ai/blog/laion-5b/) database. This model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts. With its 860M UNet and 123M text encoder, the model is relatively lightweight and runs on a GPU with at least 10GB VRAM.
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See the [model card](https://huggingface.co/CompVis/stable-diffusion) for more information.
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You need to accept the model license before downloading or using the Stable Diffusion weights. Please, visit the [model card](https://huggingface.co/CompVis/stable-diffusion-v1-3), read the license and tick the checkbox if you agree. You have to be a registered user in 🤗 Hugging Face Hub, and you'll also need to use an access token for the code to work. For more information on access tokens, please refer to [this section](https://huggingface.co/docs/hub/security-tokens) of the documentation.
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You need to accept the model license before downloading or using the Stable Diffusion weights. Please, visit the [model card](https://huggingface.co/CompVis/stable-diffusion-v1-4), read the license and tick the checkbox if you agree. You have to be a registered user in 🤗 Hugging Face Hub, and you'll also need to use an access token for the code to work. For more information on access tokens, please refer to [this section](https://huggingface.co/docs/hub/security-tokens) of the documentation.
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### Text-to-Image generation with Stable Diffusion

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