|
Download README.md from dewper/Deewper-3d-engine: direct link, hf CLI and curl.
- Browser
- Download file 2.49 kB
-
https://huggingface.co/dewper/Deewper-3d-engine/resolve/main/README.md
- Command line
-
hf download hf://dewper/Deewper-3d-engine/README.md
-
curl -L -o README.md https://huggingface.co/dewper/Deewper-3d-engine/resolve/main/README.md
2.49 kB
| 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 | |
|  | |
| 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, distressing, or offensive; or content that propagates historical or current stereotypes. |