Update docs/description.md

docs/description.md

@@ -1,5 +1,5 @@
 This demo showcases a lightweight Stable Diffusion model (SDM) for general-purpose text-to-image synthesis. Our model **BK-SDM-Small** achieves **36% reduced** parameters and latency. This model is bulit with (i) removing several residual and attention blocks from the U-Net of SDM-v1.4 and (ii) distillation pretraining on only 0.22M LAION pairs (fewer than 0.1% of the full training set). Despite very limited training resources, our model can imitate the original SDM by benefiting from transferred knowledge.
-
+Our compressed model accelerates inference speed while preserving visually compelling results.
 <center>
     <img alt="U-Net architectures and KD-based pretraining" img src="https://huggingface.co/spaces/nota-ai/theme/resolve/3bb3eed8b911d0baf306767bb9548bf732052c53/docs/compressed_stable_diffusion/fig_model.png" width="65%">
 </center>
@@ -9,11 +9,12 @@ This demo showcases a lightweight Stable Diffusion model (SDM) for general-purpo
 
 ### Notice
  - This research was accepted to
-    - [**ICML2023 Workshop on Efficient Systems for Foundation Models** (ES-FoMo)](https://es-fomo.com/)
+    - [**ICML 2023 Workshop on Efficient Systems for Foundation Models** (ES-FoMo)](https://es-fomo.com/)
     - [**ICCV 2023 Demo Track**](https://iccv2023.thecvf.com/)
  - Please be aware that your prompts are logged (_without_ any personally identifiable information).
- - For different images with the same prompt, please change _Random Seed_ in Advanced Settings (because of using the firstly sampled latent code for each seed).
- - Many parts of the demo codes were borrowed from [stabilityai/stable-diffusion](https://huggingface.co/spaces/stabilityai/stable-diffusion) and [akhaliq/small-stable-diffusion-v0](https://huggingface.co/spaces/akhaliq/small-stable-diffusion-v0). Thanks, Stability AI ([@stabilityai](https://huggingface.co/stabilityai)) and AK ([@akhaliq](https://huggingface.co/akhaliq))!
+ - For different images with the same prompt, please change _Random Seed_ in Advanced Settings (because of using the firstly sampled latent code per seed).
+ - Some demo codes were borrowed from the repo of Stability AI ([stabilityai/stable-diffusion](https://huggingface.co/spaces/stabilityai/stable-diffusion)) and AK ([akhaliq/small-stable-diffusion-v0](https://huggingface.co/spaces/akhaliq/small-stable-diffusion-v0)). Thanks!
 
-### Updates
- - [May/31/2023] The demo is running on **T4-small** (4 vCPU · 15 GB RAM · 16GB VRAM). It takes 5~10 seconds for the original model to generate a 512×512 image with 25 denoising steps. Our compressed model accelerates inference speed while preserving visually compelling results.
+### Compute environment for the demo
+ - [June/30/2023] **Free CPU-basic** (2 vCPU · 16 GB RAM) — quite slow inference.
+ - [May/31/2023] **T4-small** (4 vCPU · 15 GB RAM · 16GB VRAM) — 5~10 sec for the original model to generate a 512×512 image with 25 denoising steps.