Update README.md

README.md

@@ -1,8 +1,13 @@
+## Karlo v1 alpha
+
+Karlo is a text-conditional image generation model based on OpenAI's unCLIP architecture with the improvement over the standard super-resolution model from 64px to 256px, recovering high-frequency details only in the small number of denoising steps.
+
+
+Karlo is available in diffusers!
+
 ```python
 from diffusers import UnCLIPPipeline
 import torch
-import random
-import numpy as np
 
 pipe = UnCLIPPipeline.from_pretrained("fusing/karlo_unclip", torch_dtype=torch.float16)
 pipe = pipe.to('cuda')
@@ -11,7 +16,12 @@ prompt = "a high-resolution photograph of a big red frog on a green leaf."
 
 image = pipe([prompt]).images[0]
 
-image.save("/home/patrick_huggingface_co/images/frog.png")
+image.save("./frog.png")
 ```
 
-![img](https://huggingface.co/datasets/patrickvonplaten/images/resolve/main/frog.png)
+![img](https://huggingface.co/datasets/patrickvonplaten/images/resolve/main/frog.png)
+
+[Original codebase](https://github.com/kakaobrain/karlo)
+
+This alpha version of Karlo is trained on 115M image-text pairs, including [COYO](https://github.com/kakaobrain/coyo-dataset)-100M high-quality subset, CC3M, and CC12M. For those who are interested in a better version of Karlo trained on more large-scale high-quality datasets, please visit the landing page of our application [B^DISCOVER](https://bdiscover.kakaobrain.com/).
+