Saltar al contenido
ModelPublicadoExterno
Descargar

TripoSR

> Try our new model: SF3D with several improvements such as faster generation and more game-ready assets. > > The model is available here and we also have a demo.

TipoOtherVersiónRevision f1ccd24Bcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
1,56 GB
Versión
vRevision f1ccd24
Actualizado
1 nov 2026
Descargas
0
Fuente
Hugging Face

Descripción de la fuente

Try our new model: SF3D with several improvements such as faster generation and more game-ready assets.

The model is available here and we also have a demo.

TripoSR

TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI.

Model Details

Model Description

We closely follow LRM network architecture for the model design, where TripoSR incorporates a series of technical advancements over the LRM model in terms of both data curation as well as model and training improvements. For more technical details and evaluations, please refer to our tech report.

  • Developed by: Stability AI, Tripo AI
  • Model type: Feed-forward 3D reconstruction from a single image
  • License: MIT
  • Hardware: We train TripoSR for 5 days on 22 GPU nodes each with 8 A100 40GB GPUs

Model Sources

Training Dataset

We use renders from the Objaverse dataset, utilizing our enhanced rendering method that more closely replicate the distribution of images found in the real world, significantly improving our model’s ability to generalize. We selected a carefully curated subset of the Objaverse dataset for the training data, which is available under the CC-BY license.

Usage

Misuse, Malicious Use, and Out-of-Scope Use

The model should not be used to intentionally create or disseminate 3D models that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.

Fuentes

1 fuente
Hugging FacePrincipalVersión f1ccd24b3be18ef7ac33560e3c6656f9521d67a7
huggingface.co/Manojb/TripoSR/tree/f1ccd24b3be18ef7ac33560e3c6656f9521d67a7

Verificado 1 nov

Download files

Repository files

File inventory only; completeness is unverified.

Artefactos del modelo

1 artefacto

model.ckpt

ckpt · 1,56 GB · SHA-256 429e2c6b22a0…70ee · Hugging Face

Download file

Extractos de fuentes

3 extractos

--- datasets: - allenai/objaverse tags: - 3d extra_gated_fields: Name: text Email: text Country: text Organization or Affiliation: text I ALLOW Stability AI to email me about new model releases: checkbox license: mit pipeline_tag: image-to-3d --- > Try our new model: **SF3D** with several improvements such as faster generation and more game-ready assets. > > The model is available [here](https://huggingface.co/stabilityai/stable-fast-3d) and we also have a [demo](https://huggingface.co/spaces/stabilityai/stable-fast-3d). # TripoSR ![](figures/input800.mp4) TripoSR is a fast and feed-forward 3D generative model developed in collaboration between Stability AI and Tripo AI. ## Model Details ### Model Description We closely follow [LRM](https://arxiv.org/abs/2311.04400) network architecture for the model design, where TripoSR incorporates a series of technical advancements over the LRM model in terms of both data curation as well as model and training improvements. For more technical details and evaluations, please refer to [our tech report](https://arxiv.org/abs/2403.02151). * **Developed by**: [Stability AI](https://stability.ai/), [Tripo AI](https://tripo3d.ai/) * **Model type**: Feed-forward 3D reconstruction from a single image * **License**: MIT * **Hardware**: We train `TripoSR` for 5 days on 22 GPU nodes each with 8 A100 40GB GPUs ### Model Sources * **Repository**: https://github.com/VAST-AI-Research/TripoSR * **Tech report**: https://arxiv.org/abs/2403.02151 * **Demo**: https://huggingface.co/spaces/stabilityai/TripoSR ### Training Dataset We use renders from the [Objaverse](https://objaverse.allenai.org/objaverse-1.0) dataset, utilizing our enhanced rendering method that more closely replicate the distribution of images found in the real world, significantly improving our model’s ability to generalize. We selected a carefully curated subset of the Objaverse dataset for the training data, which is available under the CC-BY license. ## Usage * For usage instructions, please refer to our [TripoSR GitHub repository](https://github.com/VAST-AI-Research/TripoSR) * You can also try it in [our gradio demo](https://huggingface.co/spaces/stabilityai/TripoSR) ### Misuse, Malicious Use, and Out-of-Scope Use The model should not be used to intentionally create or disseminate 3D models that people would foreseeably find disturbing, distressin...

Source context: 0 downloads · 0 likes · Pipeline image-to-3d · Repo Manojb/TripoSR

Source context: 3 downloads · 0 likes · Pipeline image-to-3d · Repo Manojb/TripoSR