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@ -75,7 +75,7 @@ for the self- and cross-attention layers in the U-Net and autoencoder.
Stable Diffusion models are general text-to-image diffusion models and therefore mirror biases and (mis-)conceptions that are present Stable Diffusion models are general text-to-image diffusion models and therefore mirror biases and (mis-)conceptions that are present
in their training data. Although efforts were made to reduce the inclusion of explicit pornographic material, **we do not recommend using the provided weights for services or products without additional safety mechanisms and considerations. in their training data. Although efforts were made to reduce the inclusion of explicit pornographic material, **we do not recommend using the provided weights for services or products without additional safety mechanisms and considerations.
The weights are research artifacts and should be treated as such.** The weights are research artifacts and should be treated as such.**
Details on the training procedure and data, as well as the intended use of the model can be found in the corresponding [model card](modelcard.md). Details on the training procedure and data, as well as the intended use of the model can be found in the corresponding [model card](https://huggingface.co/stabilityai/stable-diffusion-2).
The weights are available via [the StabilityAI organization at Hugging Face](https://huggingface.co/StabilityAI) under the [CreativeML Open RAIL++-M License](LICENSE-MODEL). The weights are available via [the StabilityAI organization at Hugging Face](https://huggingface.co/StabilityAI) under the [CreativeML Open RAIL++-M License](LICENSE-MODEL).