Update README.md

README.md

@@ -10,10 +10,7 @@ tags:
 This is a Diffusers-compatible version of [Yiffymix v51 by chilon249](https://civitai.com/models/3671?modelVersionId=658237).
  See the original page for more information.
 
- Keep in mind that this is [SDXL-Lightning](https://huggingface.co/ByteDance/SDXL-Lightning) checkpoint model,
- so using fewer steps (around 12 to 25) and low guidance
- scale (around 4 to 6) is recommended for the best result.
- It's also recommended to use clip skip of 2.
+ Keep in mind that this is [SDXL-Lightning](https://huggingface.co/ByteDance/SDXL-Lightning) checkpoint model, so using fewer steps (around 12 to 25) and low guidance scale (around 4 to 6) is recommended for the best result. It's also recommended to use clip skip of 2.
 
 This repository uses DPM++ 2M Karras as its sampler (Diffusers only). 
 
@@ -50,8 +47,7 @@ Feel free to edit the image's configuration with your desire.
 
 You can see all available schedulers [here](https://huggingface.co/docs/diffusers/v0.11.0/en/api/schedulers/overview).
 
-To use scheduler other than DPM++ 2M Karras for this repository, make sure to import the
-corresponding pipeline for the scheduler you want to use. For example, we want to use Euler. First, import [EulerDiscreteScheduler](https://huggingface.co/docs/diffusers/v0.29.2/en/api/schedulers/euler#diffusers.EulerDiscreteScheduler) from Diffusers by adding this line of code.
+To use scheduler other than DPM++ 2M Karras for this repository, make sure to import the corresponding pipeline for the scheduler you want to use. For example, we want to use Euler. First, import [EulerDiscreteScheduler](https://huggingface.co/docs/diffusers/v0.29.2/en/api/schedulers/euler#diffusers.EulerDiscreteScheduler) from Diffusers by adding this line of code.
 ```py
 from diffusers import StableDiffusionXLPipeline, EulerDiscreteScheduler
 ```
@@ -84,15 +80,9 @@ pipeline = StableDiffusionXLPipeline.from_pretrained(
            ).to("cuda")
 ```
 ## Variational Autoencoder (VAE) Installation 🖼
-There are two ways to get [Variational Autoencoder (VAE)](https://huggingface.co/learn/computer-vision-course/en/unit5/generative-models/variational_autoencoders) file into the model. The first one
-is to download the file manually and the second one is to remotely download the file using code. In this repository,
-I'll explain the method of using code as the efficient way. First step is to download the VAE file.
-You can download the file manually or remotely, but I recommend you to use the remote one. Usually, VAE
-files are in .safetensors format. There are two websites you can visit to download VAE. Those are HuggingFace
-and [CivitAI](civitai.com).
+There are two ways to get [Variational Autoencoder (VAE)](https://huggingface.co/learn/computer-vision-course/en/unit5/generative-models/variational_autoencoders) file into the model. The first one is to download the file manually and the second one is to remotely download the file using code. In this repository, I'll explain the method of using code as the efficient way. First step is to download the VAE file. You can download the file manually or remotely, but I recommend you to use the remote one. Usually, VAE files are in .safetensors format. There are two websites you can visit to download VAE. Those are HuggingFace and [CivitAI](civitai.com).
 ### From HuggingFace 😊
-This method is pretty straightforward. Pick any VAE's repository you like. Then, navigate to "Files" and
-the VAE's file. Make sure to click the file.
+This method is pretty straightforward. Pick any VAE's repository you like. Then, navigate to "Files" and the VAE's file. Make sure to click the file.
 
 Click the "Copy Download Link" for the file, you'll need this.
 
@@ -119,13 +109,11 @@ pipeline = StableDiffusionXLPipeline.from_pretrained(
            model, torch_dtype=torch.float16,
            vae=vae).to("cuda")
 ```
-For manual download, just fill the `link` variable or any string variables you use to
-load the VAE file with path directory of the .safetensors.
+For manual download, just fill the `link` variable or any string variables you use to load the VAE file with path directory of the .safetensors.
 
 ##### <b></small>Troubleshooting</b></small> 🔧
 
-In case if you're experiencing `HTTP404` error because
-the program can't resolve your link, here's a simple fix.
+In case if you're experiencing `HTTP404` error because the program can't resolve your link, here's a simple fix.
 
 First, download [huggingface_hub](https://huggingface.co/docs/huggingface_hub/en/index) using `pip`.
 ```py
@@ -146,18 +134,12 @@ vae = AutoencoderKL.from_single_file(
 # use 'torch_dtype=torch.float16' for FP16.
 # add 'subfolder="folder_name"' argument if the VAE is in specific folder.
 ```
-You can use [hf_hub_download()](https://huggingface.co/docs/huggingface_hub/en/guides/download) from [huggingface_hub](https://huggingface.co/docs/huggingface_hub/en/index)
-casually without the need to check if previous method returns `HTTP404` error.
+You can use [hf_hub_download()](https://huggingface.co/docs/huggingface_hub/en/guides/download) from [huggingface_hub](https://huggingface.co/docs/huggingface_hub/en/index) casually without the need to check if previous method returns `HTTP404` error.
 ### From CivitAI 🇨
-It's trickier if the VAE is in [CivitAI](civitai.com), because you can't use
-`from_single_file()` method. It only works for files inside HuggingFace and local files only. You can upload the VAE from there into
-HuggingFace, but you must comply with the model's license before continuing. To solve this issue, you may
-use `wget` or `curl` command to get the file from outside HuggingFace.
-
-Before downloading, to organize the VAE file you want to use and download, change
-the directory to save the downloaded model with `cd`.
-Use `-O` option before specifying the file's link and name. It's the same thing
-for both `wget` and `curl`. 
+It's trickier if the VAE is in [CivitAI](civitai.com), because you can't use `from_single_file()` method. It only works for files inside HuggingFace and local files only. You can upload the VAE from there into HuggingFace, but you must comply with the model's license before continuing. To solve this issue, you may use `wget` or `curl` command to get the file from outside HuggingFace.
+
+Before downloading, to organize the VAE file you want to use and download, change the directory to save the downloaded model with `cd`.
+Use `-O` option before specifying the file's link and name. It's the same thing for both `wget` and `curl`. 
 ```py
 # For 'wget'
 !cd <path>; wget -O [filename.safetensors] <link>
@@ -170,9 +152,7 @@ for both `wget` and `curl`.
 # Windows Shell, you don't need the exclamation mark (!).
 ```
 
-Since the file is now in your local directory, you can
-finally use `from_single_file()` method normally. Make sure to
-input the correct path for your VAE file. Load the VAE file into [AutoencoderKL](https://huggingface.co/docs/diffusers/en/api/models/autoencoderkl).
+Since the file is now in your local directory, you can finally use `from_single_file()` method normally. Make sure to input the correct path for your VAE file. Load the VAE file into [AutoencoderKL](https://huggingface.co/docs/diffusers/en/api/models/autoencoderkl).
 ```py
 path = "path to VAE" # Ends with .safetensors file format.
 model = "IDK-ab0ut/Yiffymix_v51"