๐Ÿš€
Space

TripoSR

by stabilityai hf-dataset--stabilityai--triposr
Nexus Index
45.9 Top 100%
S / A / P / R / Q Breakdown Calibration Pending

Pillar scores are computed during the next indexing cycle.

Tech Context
Vital Performance
0 DL / 30D
0.0%
gradio SDK
CPU Hardware
Running Status
- Activity
Space Information Summary
Entity Passport
Registry ID hf-dataset--stabilityai--triposr
License MIT
Provider huggingface
๐Ÿ“œ

Cite this space

Academic & Research Attribution

BibTeX
@misc{hf_dataset__stabilityai__triposr,
  author = {stabilityai},
  title = {TripoSR Space},
  year = {2026},
  howpublished = {\url{https://huggingface.co/datasets/stabilityai/triposr}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
stabilityai. (2026). TripoSR [Space]. Free2AITools. https://huggingface.co/datasets/stabilityai/triposr

๐Ÿ”ฌTechnical Deep Dive

Full Specifications [+]

โš–๏ธ Nexus Index V2.0

45.9
ESTIMATED IMPACT TIER
Semantic (S) 0
Authority (A) 0
Popularity (P) 0
Recency (R) 0
Quality (Q) 0

๐Ÿ’ฌ Index Insight

FNI V2.0 for TripoSR: Semantic (S:0), Authority (A:0), Popularity (P:0), Recency (R:0), Quality (Q:0).

Free2AITools Nexus Index

Verification Authority

Unbiased Data Node Refresh: VFS Live

Environment Profile

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 modelโ€™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.

Social Proof

HuggingFace Hub
28.6KDownloads
๐Ÿ”„ Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

๐Ÿ“Š FNI Methodology ๐Ÿ“š Knowledge Baseโ„น๏ธ Verify with original source

๐Ÿ›ก๏ธ Space Transparency Report

Verified data manifest for traceability and transparency.

100% Data Disclosure Active

๐Ÿ†” Identity & Source

id
hf-dataset--stabilityai--triposr
slug
stabilityai--triposr
source
huggingface
author
stabilityai
license
MIT
tags
3d, image-to-3d, dataset:allenai/objaverse, arxiv:2311.04400, arxiv:2403.02151, license:mit, region:us

โš™๏ธ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
image-to-3d

๐Ÿ“Š Engagement & Metrics

downloads
28,641
stars
572
forks
0

Free2AITools Constitutional Data Pipeline: Curated disclosure mode active. (V15.x Standard)