Create README.md

README.md

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+---
+license: creativeml-openrail-m
+tags:
+- coreml
+- stable-diffusion
+- text-to-image
+---
+
+# Core ML Converted Model
+This model was converted to Core ML for use on Apple Silicon devices by following Apple's instructions [here](https://github.com/apple/ml-stable-diffusion#-converting-models-to-core-ml).<br>
+Provide the model to an app such as [Mochi Diffusion](https://github.com/godly-devotion/mochi-diffusion) to generate images.<br>
+
+`split_einsum` version is compatible with all compute unit options including Neural Engine.<br>
+`original` version is only compatible with CPU & GPU option.
+
+**Analog Diffusion**
+![Header](https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/images/page1.jpg)
+[*CKPT DOWNLOAD LINK*](https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/analog-diffusion-1.0.ckpt) - This is a dreambooth model trained on a diverse set of analog photographs.
+
+In your prompt, use the activation token: `analog style`
+
+You may need to use the words `blur` `haze` `naked` in your negative prompts. My dataset did not include any NSFW material but the model seems to be pretty horny. Note that using `blur` and `haze` in your negative prompt can give a sharper image but also a less pronounced analog film effect.
+
+Trained from 1.5 with VAE.
+
+Please see [this document where I share the parameters (prompt, sampler, seed, etc.) used for all example images.](https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/parameters_used_examples.txt)
+
+## Gradio
+
+We support a [Gradio](https://github.com/gradio-app/gradio) Web UI to run Analog-Diffusion:
+
+[Open in Spaces](https://huggingface.co/spaces/akhaliq/Analog-Diffusion)
+
+
+![Environments Example](https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/images/page2.jpg)
+![Characters Example](https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/images/page3.jpg)
+
+Here's a [link to non-cherrypicked batches.](https://imgur.com/a/7iOgTFv)