Update README.md

README.md

@@ -10,15 +10,25 @@ tags:
   - safetensors
 ---
 
-# RelayVSR X2
+# RelayVSR_X2
 
 We trained this RelayVSR model for **native, fixed 2× video super-resolution**.
-It doubles the input video's width and height; for example, a 768 × 1344 video
-becomes 1536 × 2688.
+It doubles the input video's width and height.
+
+We found that RelayVSR's model design is effective at suppressing temporal flicker
+in upscaled videos. This is particularly useful for videos produced by generative
+video models: the generated video may occasionally contain subtle flicker, which
+super-resolution algorithms can amplify.
 
 The [original RelayVSR model](https://huggingface.co/kopper/RelayVSR) uses a fixed
-4× super-resolution scale. This repository provides our separately trained 2×
-variant, with inference supported by [LightX2V](https://github.com/ModelTC/LightX2V).
+4× super-resolution scale, which incurs substantial inference time. To reduce this
+cost, we modified the model architecture and continued training to obtain a
+**fixed 2× RelayVSR model**, with inference supported by
+[LightX2V](https://github.com/ModelTC/LightX2V).
+
+We recommend RelayVSR as a super-resolution post-processing model for video
+generators such as **MiniMax-H3**. For example, a MiniMax-H3 video generated at
+**768 × 1344** can be upscaled by 2× to **1536 × 2688**.
 
 For inference instructions, see the
 [LightX2V RelayVSR documentation](https://github.com/ModelTC/LightX2V/tree/main/scripts/relayvsr).