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README.md
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- stable-diffusion
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- text-to-image
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- diffusers
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thumbnail: "https://huggingface.co/
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inference: false
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---
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@@ -16,22 +16,13 @@ This is the fine-tuned Stable Diffusion 1.5 model trained on classic Christmas s
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Use the tokens
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`rbsm style`
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in your prompts for the effect.
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Trained on Stability.ai's 1.5 model
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**Characters rendered with the model:**
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![
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![
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![Landscape 1](https://huggingface.co/nitrosocke/Future-Diffusion/resolve/main/images/future-diffusion-samples03s.png)
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#### Prompt and settings for the Characters:
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**future style [subject] Negative Prompt: duplicate heads bad anatomy**
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_Steps: 20, Sampler: Euler a, CFG scale: 7, Size: 512x704_
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#### Prompt and settings for the Landscapes:
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**future style city market street level at night Negative Prompt: blurry fog soft**
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_Steps: 20, Sampler: Euler a, CFG scale: 7, Size: 1024x576_
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This model was trained using fast-DreamBooth colab by TheLastBen with text_trainer_encoder for 10 and 8000 steps.
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- stable-diffusion
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- text-to-image
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- diffusers
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thumbnail: "https://huggingface.co/budbudbud/Holiday_Stop_Motion/blob/main/Santa.png"
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inference: false
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---
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Use the tokens
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`rbsm style`
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in your prompts for the effect.
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Trained on Stability.ai's 1.5 model with 768x768 resolution.
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**Characters rendered with the model:**
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![rbsm style christmas sloth, tilt shift](https://huggingface.co/budbudbud/Holiday_Stop_Motion/blob/main/Christmas_Sloth.png)
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![portrait of a (rbsm style) portrait of model Santa, classic tv, cinematic, ultrafine, colorful, by sony canon nikon f1.8, high quality, Greg Rutkowski, oil on canvas, award winning, trending, fine art photo, octane render, getty, by sony canon nikon f1.8, by Beeple and Justin Gerard, cinematic, ultrafine, colorful, poster, picture](https://huggingface.co/budbudbud/Holiday_Stop_Motion/blob/main/Santa.png)
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![(rbsm style) happy Christmas cat](https://huggingface.co/budbudbud/Holiday_Stop_Motion/blob/main/Christmas_Cat.png)
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![rbsm style superman, tv still](https://huggingface.co/budbudbud/Holiday_Stop_Motion/blob/main/Superman.png)
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This model was trained using fast-DreamBooth colab by TheLastBen with text_trainer_encoder for 10 and 8000 steps.
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