Fix formatting

README.md

@@ -25,7 +25,6 @@ This model was trained on a dataset of **80,000** safe anime prompts for 3 epoch
 I didn't release the V1 model because it only generated gibberish prompts. After trying all means to correct that behavior, I eventually figured that the cause of the gibberish prompts is not from the pipeline params, model structure or training duration, but rather from the random usernames in the training data. 
 Here's the complete [prompt preprocessing algorithm](./preprocess.py).
 
-[Danbooru model](https://huggingface.co/FredZhang7/danbooru-tag-generator)
 
 ## Text-to-image Examples
 
@@ -77,4 +76,7 @@ Please see [Fast GPT PromptGen](https://huggingface.co/FredZhang7/distilgpt2-sta
 - If you feel like a generated anime character doesn't show emotions, try emoticons like `;o`, `:o`, `;p`, `:d`, `:p`, and `;d` in the prompt.
 I also use `happy smirk`, `happy smile`, `laughing closed eyes`, etc. to make the characters more lively and expressive.
 
-- Adding `absurdres`, instead of `highres` and `masterpiece`, to a prompt can drastically increase the sharpness and resolution of a generated image.
+- Adding `absurdres`, instead of `highres` and `masterpiece`, to a prompt can drastically increase the sharpness and resolution of a generated image.
+
+## Danbooru
+[Link to the Danbooru version](https://huggingface.co/FredZhang7/danbooru-tag-generator)