---
license: mit
pipeline_tag: image-to-3d
base_model: stabilityai/TripoSR
tags:
- lux3d
- rust
- candle
- safetensors
- canonical-weights
- 3d
- image-to-3d
- mesh-generation
- triposr
---

# Lux3D TripoSR Canonical Weights

This repository contains the canonicalized `safetensors` export of the TripoSR checkpoint used by the Lux3D runtime.

## Model Details

- Model family: `triposr`
- Canonical file: `model.safetensors`
- Tensor count: `549`
- Primary runtime target: Lux3D runtime
- Typical output: mesh export (`.obj`)

## Included Files

- `model.safetensors`
- `resolved_config.json`
- `manifest.json`
- `checksums.json`

## Usage With Lux3D

The Lux3D CLI can validate and use the package once it is installed into your local model asset layout.

```powershell
cargo run -p lux3d-cli -- inspect --repo-root <runtime-root> triposr
cargo run -p lux3d-cli -- run --repo-root <runtime-root> triposr --source <input-image> --mc-resolution 256 --mc-threshold 25.0 --output <output-file.obj>
```

## Provenance

- Upstream source model: [`stabilityai/TripoSR`](https://huggingface.co/stabilityai/TripoSR)
- Canonicalization flow: `tools/python_baseline/normalize_weights.py`

The exact source checksum set is recorded in `manifest.json`. The integrity of the uploaded package is recorded in `checksums.json`.

## Intended Use

- single-image 3D reconstruction with Lux3D
- mesh generation workflows using canonical weights
- reproducible runtime validation

## Limitations

- Verified Lux3D runtime inference currently assumes CUDA.
- This package includes canonical runtime artifacts only.
- Texture baking and other extended upstream utilities are outside the scope of this package.

## License

- Upstream model page: [`stabilityai/TripoSR`](https://huggingface.co/stabilityai/TripoSR)
- License file in this repository: [LICENSE](LICENSE)

## Citation

```bibtex
@article{tripoSR2024,
  title={TripoSR: Fast 3D Object Reconstruction from a Single Image},
  author={Tochilkin, Dmitry and Pankratz, David and Liu, Zexiang and Huang, Zixuan and Letts, Adam and Li, Yangguang and Liang, Ding and Laforte, Christian and Jampani, Varun and Cao, Yan-Pei},
  journal={arXiv preprint arXiv:2403.02151},
  year={2024}
}
```