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--- |
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license: creativeml-openrail-m |
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tags: |
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- coreml |
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- stable-diffusion |
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- text-to-image |
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--- |
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# Core ML Converted Model |
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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> |
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Provide the model to an app such as [Mochi Diffusion](https://github.com/godly-devotion/MochiDiffusion) to generate images.<br> |
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`split_einsum` version is compatible with all compute unit options including Neural Engine.<br> |
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`original` version is only compatible with CPU & GPU option. |
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**Analog Diffusion** |
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![Header](https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/images/page1.jpg) |
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[*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. |
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In your prompt, use the activation token: `analog style` |
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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. |
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Trained from 1.5 with VAE. |
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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) |
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## Gradio |
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We support a [Gradio](https://github.com/gradio-app/gradio) Web UI to run Analog-Diffusion: |
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[Open in Spaces](https://huggingface.co/spaces/akhaliq/Analog-Diffusion) |
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![Environments Example](https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/images/page2.jpg) |
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![Characters Example](https://huggingface.co/wavymulder/Analog-Diffusion/resolve/main/images/page3.jpg) |
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Here's a [link to non-cherrypicked batches.](https://imgur.com/a/7iOgTFv) |
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