Update README.md

README.md

@@ -69,10 +69,7 @@ Triangles: 1497.3333333333333
 3. Use controls.json for temporal conditioning
 4. Train with diffusion models like Waypoint-1-Small
 
-This dataset is optimized for low-end device simulation and micro-scale spatial studies.
-
-# Short dataset description (one-liner for card):
-
+This dataset is optimized for low-end device simulation and micro-scale spatial studies:
 Synthetic 226-frame 1280×562 PNG sequence + metadata for training diffusion models in OVERWORLD-style environments 
 with camera pose and temporal controls; optimized for low-end / micro-scale 3D simulation.
 
@@ -91,13 +88,6 @@ of diffusion models (OVERWORLD-style = controllable 3D world generation via came
 Use it to pre-train or distill models before scaling to larger OVERWORLD-style data → enables faster iteration 
 on small hardware while preserving compatible conditioning format.
 
-# Source
-
-webXOS
-webxos.netlify.app
-github.com/webxos
-huggingface.co/webxos
-
 # License:
 
 MIT