Duplicate from coreml/coreml-cyberrealistic-v32_cn

Co-authored-by: Joel Rittvo <jrrjrr@users.noreply.huggingface.co>

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README.md

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+---
+license: creativeml-openrail-m
+tags:
+- coreml
+- stable-diffusion
+- text-to-image
+duplicated_from: coreml/coreml-cyberrealistic-v32_cn
+---
+# Core ML Converted Model:
+
+  - This model was converted to [Core ML for use on Apple Silicon devices](https://github.com/apple/ml-stable-diffusion). Conversion instructions can be found [here](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-ckpt-or-safetensors-files-to-Core-ML).
+  - Provide the model to an app such as **Mochi Diffusion** [Github](https://github.com/godly-devotion/MochiDiffusion) / [Discord](https://discord.gg/x2kartzxGv) to generate images.
+  - `split_einsum` version is compatible with all compute unit options including Neural Engine.
+  - `original` version is only compatible with `CPU & GPU` option.
+  - Custom resolution versions are tagged accordingly.
+  - The `vae-ft-mse-840000-ema-pruned.ckpt` VAE is embedded into the model.
+  - This model was converted with a `vae-encoder` for use with `image2image`.
+  - This model is `fp16`.
+  - Descriptions are posted as-is from original model source.
+  - Not all features and/or results may be available in `CoreML` format.
+  - This model does not have the [unet split into chunks](https://github.com/apple/ml-stable-diffusion#-converting-models-to-core-ml).
+  - This model does not include a `safety checker` (for NSFW content).
+  - This model can be used with ControlNet.
+
+<br>
+
+# cyberrealistic-v32_cn:
+Source(s): [CivitAI](https://civitai.com/models/15003/cyberrealistic)<br>
+
+## CyberRealistic v3.2
+
+Introducing my versatile photorealistic model - the result of a rigorous testing process that blends various models to achieve the desired output. While I cannot recall all of the individual components used in its creation, I am immensely satisfied with the end result. This model incorporates several custom elements, adding an extra layer of uniqueness to its output.
+
+One of the model's key strengths lies in its ability to effectively process textual inversions and LORA, providing accurate and detailed outputs. Additionally, the model requires minimal prompts, making it incredibly user-friendly and accessible.
+
+In this version, the core remains unchanged, although several new techniques have been introduced and certain elements have been added or removed.
+
+Once again, it's important to note that this version is not intended as a replacement for version 3.1, but rather as an alternative version.
+
+VAE recommended: sd-vae-ft-mse-original.  (Note: The VAE has been baked into the files at this repo.)<br><br>
+
+![image](https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/30cd4bac-74e9-4ac1-8b50-12110132e617/width=450/Cyber3.21.jpeg)
+
+![image](https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/81b3ab3d-d519-46a2-afea-26cd310f674e/width=450/Cyber3.213.jpeg)
+
+![image](https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/89b35f4d-058c-488f-8174-975838c0c282/width=450/Cyber3.210.jpeg)
+
+![image](https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/d8b59ae7-0e44-4e98-8d83-c99c89ae9e43/width=450/Cyber3.24.jpeg)

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