Update README.md

README.md

@@ -25,7 +25,7 @@ This repository contains a model that generates highly aesthetic images of resol
 
 **Playground v2** is a diffusion-based text-to-image generative model. The model was trained from scratch by the research team at [Playground](https://playground.com). 
 
-Playground v2’s images are favored 2.5 times more than those produced by Stable Diffusion XL, according to Playground’s [user study](#user-study).
+Playground v2’s images are favored **2.5** times more than those produced by Stable Diffusion XL, according to Playground’s [user study](#user-study).
 
 We are thrilled to release all intermediate checkpoints at different training stages, including evaluation metrics, to the community. We hope this will foster more foundation model research in pixels.
 
@@ -68,7 +68,7 @@ image  = pipe(prompt=prompt).images[0]
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63855d851769b7c4b10e1f76/8VzBkSYaUU3dt509Co9sk.png)
 
-According to user studies conducted by Playground, involving over 2,600 prompts and thousands of users, the images generated by Playground v2 are favored 2.5 times more than those produced by [Stable Diffusion XL](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0).
+According to user studies conducted by Playground, involving over 2,600 prompts and thousands of users, the images generated by Playground v2 are favored **2.5** times more than those produced by [Stable Diffusion XL](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0).
 
 We report user preference metrics on [PartiPrompts](https://github.com/google-research/parti), following standard practice, and on an internal prompt dataset curated by the Playground team. The “Internal 1K” prompt dataset is diverse and covers various categories and tasks.