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README.md

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 ---
+language:
+- en
 license: creativeml-openrail-m
+thumbnail: "https://huggingface.co/Guizmus/SDArt_AliceInDiffusionLand/resolve/main/showcase.jpg"
+tags:
+- stable-diffusion
+- text-to-image
+- image-to-image
 ---
+# SDArt : Alice in Diffusion Land (version based on 1.5)
+
+![Showcase](https://huggingface.co/Guizmus/SDArt_AliceInDiffusionLand/resolve/main/showcase.jpg)
+
+## Theme
+
+> “Alice falls down the rabbit hole and enters a digital dream”
+
+* Create an image that rips off of Alice in Wonderland, but with a technological twist! 
+How would Alice interact with the digital realm?
+* What kind of mind-bending experiences would she encounter? Will she find herself lost in a maze of code, or will she discover a new dimension in cyberspace?
+* Characters like Alice in Wonderland, Cheshire Cat, the Mad Hatter, or the Queen of Hearts– how would they appear and interact in the digital world? What sort of otherworldly environments would they inhabit? (i.e. Digital tea party, code tangled forests, holographic food)
+* Bring your skills and show out on twisting a timeless classic story into a new age tech haven!
+
+
+## Model description 
+
+This is a model related to the "Picture of the Week" contest on [Stable Diffusion discord](https://discord.gg/stablediffusion).
+
+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.
+
+The total dataset is made of 47 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.
+
+The recommended sampling is k_Euler_a or DPM++ 2M Karras on 20 steps, CFGS 7.5 .
+
+## Trained tokens
+
+* SDArt
+* pln
+* bnp
+* aten
+* fcu
+* shai
+* peth
+* cous
+* aved
+* mth
+* elio
+* gani
+* opi
+* omd
+* kuro
+* asot
+* iru
+* onex
+* psst
+* irgc
+* buka
+* mds
+* pik
+* buon
+* yel
+* muc
+* byes
+* utm
+* dany
+* pafc
+* yler
+* zaki
+* oue
+* mss
+* guin
+* pbc
+* nasi
+* pgs
+* pkg
+* mako
+* inem
+* mlas
+* isch
+* phol
+* vedi
+* acu
+* pte
+* oxi
+
+## Download links
+
+[SafeTensors](https://huggingface.co/Guizmus/SDArt_AliceInDiffusionLand/resolve/main/SDArt_AliceInDiffusionLand.safetensors)
+
+[CKPT](https://huggingface.co/Guizmus/SDArt_AliceInDiffusionLand/resolve/main/SDArt_AliceInDiffusionLand.ckpt)
+
+[Dataset](https://huggingface.co/Guizmus/SDArt_AliceInDiffusionLand/resolve/main/dataset.zip)
+
+## 🧨 Diffusers
+
+This model can be used just like any other Stable Diffusion model. For more information,
+please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion).
+
+You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX]().
+
+```python
+from diffusers import StableDiffusionPipeline
+import torch
+
+model_id = "Guizmus/SDArt_AliceInDiffusionLand"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
+prompt = "SDArt isch"
+image = pipe(prompt).images[0]
+
+image.save("./SDArt.png")
+```

dataset.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ae18ab50ecb5c1c9bfe22028c2be05d0ea35fb68f9cdfbce620cfed79a65dfd3
+size 3588173