From a79c66a407dd7996052b6c7c9d77a338380506b4 Mon Sep 17 00:00:00 2001
From: Yufan <47047889+drboog@users.noreply.github.com>
Date: Mon, 28 Mar 2022 15:42:53 -0400
Subject: [PATCH] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 43e41bc..47bf9c1 100644
--- a/README.md
+++ b/README.md
@@ -81,7 +81,7 @@ Calculating metrics:
 python calc_metrics.py --network=./some_pre-trained_models.pkl --metrics=fid50k_full,is50k --data=./training_data.zip --test_data=./testing_data.zip
 ```
 
-To generate images with pre-trained models, you can use ./generate.ipynb
+To generate images with pre-trained models, you can use ./generate.ipynb. Also, you can try this [Colab notebook](https://colab.research.google.com/github/pollinations/hive/blob/main/interesting_notebooks/LAFITE_generate.ipynb) by @[voodoohop](https://github.com/voodoohop), in which the model pre-trained on CC3M is used.
 
 To calculate SOA scores for MS-COCO, you can use ./generate_for_soa.py and [Semantic Object Accuracy for Generative Text-to-Image Synthesis](https://github.com/tohinz/semantic-object-accuracy-for-generative-text-to-image-synthesis)