Update README.md

README.md

@@ -2,9 +2,9 @@
 license: apache-2.0
 pipeline_tag: text-to-image
 ---
-# Work and train in progress!
+# Work / train in progress
 
-⚡️Waifu: Efficient High-Resolution Waifu Synthesis
+⚡️Waifu: efficient high-resolution waifu synthesis
 
 
 waifu is a free text-to-image model that can efficiently generate images in 80 languages. Our goal is to create a small model without compromising on quality.
@@ -14,7 +14,7 @@ waifu is a free text-to-image model that can efficiently generate images in 80 l
 (1) [**AuraDiffusion/16ch-vae**](https://huggingface.co/AuraDiffusion/16ch-vae): A fully open source 16ch VAE. Natively trained in fp16. \
 (2) [**Linear DiT**](https://github.com/NVlabs/Sana): we use 1.6b DiT transformer with linear attention. \
 (3) [**MEXMA-SigLIP**](https://huggingface.co/visheratin/mexma-siglip): MEXMA-SigLIP is a model that combines the [MEXMA](https://huggingface.co/facebook/MEXMA) multilingual text encoder and an image encoder from the [SigLIP](https://huggingface.co/timm/ViT-SO400M-14-SigLIP-384) model. This allows us to get a high-performance CLIP model for 80 languages.. \
-(4) Other: we use Flow-Euler sampler, Adafactor-Fused optimizer and bf16 precision for training, and combine efficient caption labeling (MoonDream, CogVlM, Human, Gpts's) and danbooru tags to accelerate convergence.
+(4) Other: we use Flow-Euler sampler, Adafactor-Fused optimizer and bf16 precision for training, and combine efficient caption labeling (MoonDream, CogVlM, Human, Gpt's) and danbooru tags to accelerate convergence.
 
 
 ## Example