Update README.md

README.md

@@ -6,40 +6,9 @@ tags:
 - 3d-generation
 - rectified-flow
 ---
-# TripoSG - High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models
+# TripoSG
 
-TripoSG is a state-of-the-art image-to-3D generation foundation model that leverages large-scale rectified flow transformers to produce high-fidelity 3D shapes from single images.
+For more details, please refer to the original repository:
+https://huggingface.co/VAST-AI/TripoSG
 
-## Model Description
-
-### Model Architecture
-
-TripoSG utilizes a novel architecture combining:
-- Rectified Flow (RF) based Transformer for stable, linear trajectory modeling
-- Advanced VAE with SDF-based representation and hybrid geometric supervision
-- Cross-attention mechanism for image feature condition
-- 1.5B parameters operating on 2048 latent tokens
-
-## Intended Uses
-
-This model is designed for:
-- Converting single images to high-quality 3D meshes
-- Creative and design applications
-- Gaming and VFX asset creation
-- Prototyping and visualization
-
-## Requirements
-
-- CUDA-capable GPU (>8GB VRAM)
-
-## Usage
-
-For detailed usage instructions, please visit our [GitHub repository](https://github.com/VAST-AI-Research/TripoSG).
-
-## About
-
-TripoSG is developed by [Tripo](https://www.tripo3d.ai), [VAST AI Research](https://github.com/orgs/VAST-AI-Research), pushing the boundaries of 3D Generative AI.
-For more information:
-- [GitHub Repository](https://github.com/VAST-AI-Research/TripoSG)
-- [Paper](https://arxiv.org/abs/2502.06608)
-- [Gradio Demo](https://huggingface.co/spaces/VAST-AI/TripoSG)
+This project is a refactored version of VAST-AI/TripoSG and is released under the same license as the original project.