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README.md
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language:
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- en
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license: creativeml-openrail-m
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thumbnail: "https://huggingface.co/Guizmus/
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tags:
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- stable-diffusion
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- text-to-image
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# PoW : Something
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![Showcase](https://huggingface.co/Guizmus/
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## Theme
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This is a model related to the "Picture of the Week" contest on Stable Diffusion discord.
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I try to make a model out of all the submission for people to continue enjoy the theme after the even, and see a little of their designs in other people's creations. The token stays "
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The total dataset is made of 50 pictures. It was trained on [Stable diffusion 1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5). I used [EveryDream](https://github.com/victorchall/EveryDream2trainer) to do the training, 100 total repeat per picture. The pictures were tagged using the token "
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The recommended sampling is k_Euler_a or DPM++ 2M Karras on 20 steps, CFGS 7.5 .
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## Trained tokens
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## Download links
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[SafeTensors](https://huggingface.co/Guizmus/
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[CKPT](https://huggingface.co/Guizmus/
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[Dataset](https://huggingface.co/Guizmus/
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## 🧨 Diffusers
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from diffusers import StableDiffusionPipeline
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import torch
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model_id = "Guizmus/
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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prompt = "
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image = pipe(prompt).images[0]
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image.save("./
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```
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language:
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- en
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license: creativeml-openrail-m
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thumbnail: "https://huggingface.co/Guizmus/SDArt_something/resolve/main/showcase.jpg"
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tags:
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- stable-diffusion
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- text-to-image
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---
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# PoW : Something
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![Showcase](https://huggingface.co/Guizmus/SDArt_something/resolve/main/showcase.jpg)
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## Theme
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This is a model related to the "Picture of the Week" contest on Stable Diffusion discord.
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I try to make a model out of all the submission for people to continue enjoy the theme after the even, and see a little of their designs in other people's creations. The token stays "SDArt" and I balance the learning on the low side, so that it doesn't just replicate creations.
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The total dataset is made of 50 pictures. It was trained on [Stable diffusion 1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5). I used [EveryDream](https://github.com/victorchall/EveryDream2trainer) to do the training, 100 total repeat per picture. The pictures were tagged using the token "SDArt", and an arbitrary token I choose. The dataset is provided below, as well as a list of usernames and their corresponding token.
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The recommended sampling is k_Euler_a or DPM++ 2M Karras on 20 steps, CFGS 7.5 .
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## Trained tokens
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* SDArt
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* ohwx
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* aten
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* fcu
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* cees
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* chor
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* cmdr
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* mth
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* nrf
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* elio
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* gani
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* pfa
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* kprc
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* kuro
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* ndi
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* asot
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* bsp
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* psst
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* sqm
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* irgc
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* guyz
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* hela
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* iru
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* lexa
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* dany
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* lpg
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* mede
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* mib
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* aroa
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* avel
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* vaw
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* zaki
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* nigh
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* niu
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* guin
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* urd
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* vini
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* pz
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* crit
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* siam
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* spon
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* taku
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* ufos
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* phol
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* uzzi
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* vaca
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* dds
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* yel
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* pte
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* oxi
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* yte
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## Download links
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[SafeTensors](https://huggingface.co/Guizmus/SDArt_something/resolve/main/SDArt_Something.safetensors)
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[CKPT](https://huggingface.co/Guizmus/SDArt_something/resolve/main/SDArt_Something.ckpt)
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[Dataset](https://huggingface.co/Guizmus/SDArt_something/resolve/main/dataset.zip)
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[Old version](https://huggingface.co/Guizmus/SDArt_something/resolve/main/PoWStyle-Something.safetensors)
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## 🧨 Diffusers
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from diffusers import StableDiffusionPipeline
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import torch
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model_id = "Guizmus/SDArt_something"
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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pipe = pipe.to("cuda")
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prompt = "SDArt oxi"
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image = pipe(prompt).images[0]
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image.save("./SDArt.png")
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```
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showcase.jpg
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Git LFS Details
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