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---
license: creativeml-openrail-m
language:
- en
thumbnail: >-
https://huggingface.co/TheRafal/everything-v1/resolve/main/img/thumbnail.png
pipeline_tag: text-to-image
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- image-to-image
- diffusers
- aiart
- anime
---
<center><img src="https://huggingface.co/TheRafal/everything-v1/resolve/main/img/1.png" width="768" height="768" alt="Girl on cherry blossom background" /></center>
![visitors](https://visitor-badge.glitch.me/badge?page_id=everything&left_color=red)
----
# Everything V1
Everything V1 is a fine-tuned model based on Anything V3. It was trained using Dreambooth and merged using Merge Block Weighted. Like other anime-style Stable Diffusion models, it also supports danbooru tags to generate images.
e.g. **_1girl, white hair, blue eyes, cat ears, outdoors, city_**
<details>
<summary>SHOW IMAGE</summary>
<center><img src="https://huggingface.co/TheRafal/everything-v1/resolve/main/img/example.png" width="512" height="512" alt="Example prompt" /></center>
</details>
----
# How to download
## Batch download
1. Install Git
2. Create a folder of your choice and right click → "Git bash here" and open a gitbash on the folder's directory.
3. Run the following commands in order.
```
git lfs install
git clone https://huggingface.co/TheRafal/everything
```
4. Complete
## Select and download
1. Go to the [Files and versions](https://huggingface.co/TheRafal/everything-v1/tree/main) tab in the [Everything V1 repository](https://huggingface.co/TheRafal/everything-v1)
2. Select the model you want to download
3. Download
4. Complete
----
# Diffusers
This model can be used just like any other Stable Diffusion model.
You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx) or [MPS](https://huggingface.co/docs/diffusers/optimization/mps).
```python
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained('TheRafal/everything', torch_dtype=torch.float32).to('cuda')
prompt = "masterpiece, 1girl, blonde hair, blue eyes, colorful, cumulonimbus clouds, lighting, short hair, city, hoodie, night"
with autocast("cuda"):
image = pipe(prompt, num_inference_steps=50, guidance_scale=7.5)["images"][0]
image.save(prompt.replace(" ", "_") + ".png")
```
<details>
<summary>SHOW IMAGE</summary>
**Anime Girl:**
![Anime Girl](https://huggingface.co/TheRafal/everything-v1/resolve/main/img/test.png)
</details>
----
# Examples
Below are some examples of images generated using this model:
<details>
<summary>SHOW IMAGES</summary>
**Anime Girl:**
![Anime Girl](https://huggingface.co/TheRafal/everything-v1/resolve/main/img/1girl.png)
```
1girl, red hair, blue eyes, short hair, jacket, winter clothes, scarf, outdoors, tokyo \(city\), snow, snowing, gloves, pants, looking at viewer, cowboy shot
Steps: 50, Sampler: DPM++ 2M Karras, CFG scale: 7, Seed: 2436148258, Size: 768x768
```
**Anime Boy:**
![Anime Boy](https://huggingface.co/TheRafal/everything-v1/resolve/main/img/1boy.png)
```
1boy, black hair, green eyes, bishounen, casual, indoors, sitting, coffee shop, sitting, bokeh
Steps: 50, Sampler: DPM++ 2M Karras, CFG scale: 7, Seed: 4225599226, Size: 768x768
```
</details>
----
# License
This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
The CreativeML OpenRAIL License specifies:
1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content
2. The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
[Please read the full license here](https://huggingface.co/spaces/CompVis/stable-diffusion-license)