Change README to show how to use it with diffusers (#4)

- Change README to show how to use it with diffusers (0628f4b96d2ae4dc2f55c3aa541f7db6675a5501)


Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>

README.md

@@ -13,9 +13,60 @@ This model is NOT the 19.2M images Characters Model on TrinArt, but an improved
 
 このモデルはTrinArtのキャラクターズモデル(1920万枚再学習モデル)ではありません！　とりんさまAIボットのモデルの改良版です。このモデルはオリジナルのSD v1.4モデルのアートスタイルをできる限り残したまま、アニメ・マンガ方向に調整することを意図しています。
 
-A Diffusers port of the pre-trained model is available at https://huggingface.co/ayan4m1/trinart_diffusers_v2
+## Diffusers
 
-(by ayan4m1 - thanks!)
+The model has been ported to `diffusers` by [ayan4m1](https://huggingface.co/ayan4m1] (thanks!) 
+and can easily be run from one of the branches:
+- `revision="diffusers-60k"` for the checkpoint trained on 60,000 steps,
+- `revision="diffusers-95k"` for the checkpoint trained on 95,000 steps,
+- `revision="diffusers-115k"` for the checkpoint trained on 115,000 steps.
+
+For more information, please have a look at [the "Three flavors" section](#three-flavors).
+
+### Example Text2Image
+
+```python
+# !pip install diffusers==0.3.0
+from diffusers import StableDiffusionPipeline
+
+# using the 60,000 steps checkpoint
+pipe = StableDiffusionPipeline.from_pretrained("naclbit/trinart_stable_diffusion_v2", revision="diffusers-60k")
+pipe.to("cuda")
+
+image = pipe("A magical dragon flying in front of the Himalaya in manga style").images[0]
+image
+```
+
+![dragon](https://huggingface.co/datasets/patrickvonplaten/images/resolve/main/a_magical_dragon_himalaya.png)
+
+If you want to run the pipeline faster or on a different hardware, please have a look at the [optimization docs](https://huggingface.co/docs/diffusers/optimization/fp16).
+
+### Example Image2Image
+
+```python
+# !pip install diffusers==0.3.0
+from diffusers import StableDiffusionImg2ImgPipeline
+import requests
+from PIL import Image
+from io import BytesIO
+
+url = "https://scitechdaily.com/images/Dog-Park.jpg"
+
+response = requests.get(url)
+init_image = Image.open(BytesIO(response.content)).convert("RGB")
+init_image = init_image.resize((768, 512))
+
+# using the 115,000 steps checkpoint
+pipe = StableDiffusionImg2ImgPipeline.from_pretrained("naclbit/trinart_stable_diffusion_v2", revision="diffusers-115k")
+pipe.to("cuda")
+
+images = pipe(prompt="Manga drawing of Brad Pitt", init_image=init_image, strength=0.75, guidance_scale=7.5).images
+image
+```
+
+![brad_pitt](https://huggingface.co/datasets/patrickvonplaten/images/blob/main/manga_man.png)
+
+If you want to run the pipeline faster or on a different hardware, please have a look at the [optimization docs](https://huggingface.co/docs/diffusers/optimization/fp16).
 
 
 ## Stable Diffusion TrinArt/Trin-sama AI finetune v2