Update README.md

README.md

@@ -29,43 +29,6 @@ Cells were segmented, meshed with **marching cubes** (+ Laplacian smoothing), th
 - Comes with both **mesh** and **point-cloud** views for flexible pipelines
 
 ---
-
-## Repository Layout
-
-🚀 PointMIL is an ICCV 2025 Highlight — powering interpretable 3D cell shape analysis at Sentinal4D
-
-
-
-At Sentinal4D, we’re pioneering the analysis of 3D cell shapes, and we believe models should be trustworthy by design.
-
-
-
-PointMIL is our unified Multiple Instance Learning (MIL) framework that delivers state-of-the-art accuracy across 3D biomedical datasets and inherent interpretability.
-
-
-
-Why this matters for biology
-
-- Mapping drug effects in 3D: See which cell regions the drug affects, e.g., rounding vs. elongation, lost protrusions, altered curvature.
-
-- New dataset, ATLAS-1: Drug-treated 3D melanoma cells in collagen (control, nocodazole, blebbistatin) to evaluate both performance and interpretability on real data. Available on Hugging Face 🤗 
-
-- Higher accuracy than black-box models. 
-
-- Plug-in head: Works with popular point-cloud backbones.
-
-
-
-Try it for yourself:
-
-🌐 Project page + live demo: https://sentinal4d.github.io/PointMIL/
-
-💾 Code: https://github.com/Sentinal4D/PointMIL/
-
-🧪 Dataset (ATLAS-1): https://sentinal4d.github.io/ATLAS-1/
-
-If you work on cell morphology, drug discovery, or explainable 3D AI, we’d love your feedback and collaborations.
-
-
-
-#ICCV2025 #Sentinal4D #PointMIL #3D #CellBiology #Morphology #ExplainableAI #XAI #ComputerVision #MIL #OpenScience
+To download:
+```bash
+hf download --repo-type dataset Sentinal4D/ATLAS-1 --local-dir ./