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README.md

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----
-license: mit
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+---
+license: mit
+pipeline_tag: image-to-3d
+tags:
+- triposg
+- 3d-generation
+- rectified-flow
+---
+# TripoSG - High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models
+
+TripoSG-scribble is a variant of 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.
+
+## 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
+
+TripoSG-scribble accepts scribble image and text prompt condition. For inference efficiency, TripoSG-scribble is different from TripoSG in:
+- TripoSG-scribble is a CFG-distilled model and should be used with CFG=0
+- TripoSG-scribble is trained with 512 latent tokens
+
+## Intended Uses
+
+This model is designed for:
+- Converting scribble image and text prompt 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-scribble 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-scribble)