fix: correct CSS property & missing articles (#152)

- Correct "border-raduis" to "border-radius"
- Insert missing article "a" in "modern giant diffusion model"
- Insert missing article "a" in "decoder-only small LLM"

README.md

@@ -13,7 +13,7 @@
   <a href="https://discord.gg/rde6eaE5Ta"><img src="https://img.shields.io/static/v1?label=Discuss&message=Discord&color=purple&logo=discord"></a> &ensp;
 </div>
 
-<p align="center" border-raduis="10px">
+<p align="center" border-radius="10px">
   <img src="asset/Sana.jpg" width="90%" alt="teaser_page1"/>
 </p>
 
@@ -25,10 +25,10 @@ Core designs include:
 
 (1) [**DC-AE**](https://hanlab.mit.edu/projects/dc-ae): unlike traditional AEs, which compress images only 8×, we trained an AE that can compress images 32×, effectively reducing the number of latent tokens. \
 (2) **Linear DiT**: we replace all vanilla attention in DiT with linear attention, which is more efficient at high resolutions without sacrificing quality. \
-(3) **Decoder-only text encoder**: we replaced T5 with modern decoder-only small LLM as the text encoder and designed complex human instruction with in-context learning to enhance the image-text alignment. \
+(3) **Decoder-only text encoder**: we replaced T5 with a modern decoder-only small LLM as the text encoder and designed complex human instruction with in-context learning to enhance the image-text alignment. \
 (4) **Efficient training and sampling**: we propose **Flow-DPM-Solver** to reduce sampling steps, with efficient caption labeling and selection to accelerate convergence.
 
-As a result, Sana-0.6B is very competitive with modern giant diffusion model (e.g. Flux-12B), being 20 times smaller and 100+ times faster in measured throughput. Moreover, Sana-0.6B can be deployed on a 16GB laptop GPU, taking less than 1 second to generate a 1024 × 1024 resolution image. Sana enables content creation at low cost.
+As a result, Sana-0.6B is very competitive with modern giant diffusion models (e.g. Flux-12B), being 20 times smaller and 100+ times faster in measured throughput. Moreover, Sana-0.6B can be deployed on a 16GB laptop GPU, taking less than 1 second to generate a 1024 × 1024 resolution image. Sana enables content creation at low cost.
 
 <p align="center" border-raduis="10px">
   <img src="asset/model-incremental.jpg" width="90%" alt="teaser_page2"/>