🧠
Model

DIGITS

by NVIDIA gh-model--nvidia--digits
Nexus Index
39.3 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 73
R: Recency 39
Q: Quality 50
Tech Context
Vital Performance
0 DL / 30D
0.0%
Audited 39.3 FNI Score
Tiny - Params
- Context
0 Downloads
Restricted BSD License
Model Information Summary
Entity Passport
Registry ID gh-model--nvidia--digits
License BSD-3-Clause
Provider github
📜

Cite this model

Academic & Research Attribution

BibTeX
@misc{gh_model__nvidia__digits,
  author = {NVIDIA},
  title = {DIGITS Model},
  year = {2026},
  howpublished = {\url{https://github.com/nvidia/digits}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
NVIDIA. (2026). DIGITS [Model]. Free2AITools. https://github.com/nvidia/digits

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🐙 Git Clone
git clone https://github.com/nvidia/digits

âš–ī¸ Nexus Index V2.0

39.3
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 73
Recency (R) 39
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for DIGITS: Semantic (S:50), Authority (A:0), Popularity (P:73), Recency (R:39), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

Unbiased Data Node Refresh: VFS Live
---

🚀 What's Next?

Technical Deep Dive

DIGITS

DIGITS (the Deep Learning GPU Training System) is a webapp for training deep learning models.

Note: We are no longer adding features, fixing bugs, or supporting the NVIDIA Deep Learning GPU Training System (DIGITS) software. You may continue to use the software if it meets your needs. However:

  • For developers creating vision AI applications, we suggest NVIDIA TAO, an open source toolkit for AI model training and customization. Learn more about NVIDIA TAO.
  • For developers interested in NVIDIA Project DIGITS, to learn more, visit NVIDIA Project DIGITS.

Feedback

In addition to submitting pull requests, feel free to submit and vote on feature requests via our ideas portal.

Documentation

Current and most updated document is available at NVIDIA Accelerated Computing, Deep Learning Documentation, NVIDIA DIGITS.

Installation

Installation method Supported platform[s] Available versions Instructions
Source Ubuntu 14.04, 16.04 GitHub tags docs/BuildDigits.md

Official DIGITS container is available at nvcr.io via docker pull command.

Usage

Once you have installed DIGITS, visit docs/GettingStarted.md for an introductory walkthrough.

Then, take a look at some of the other documentation at docs/ and examples/:

Get help

Installation issues

  • First, check out the instructions above
  • Then, ask questions on our user group

Usage questions

Bugs and feature requests

Notice on security

Users shall understand that DIGITS is not designed to be run as an exposed external web service.

âš ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

GitHub Repository
4.2KStars
🔄 Daily sync (03:00 UTC)

AI Summary: Based on GitHub metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseâ„šī¸ Verify with original source

đŸ›Ąī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
gh-model--nvidia--digits
slug
nvidia--digits
source
github
author
NVIDIA
license
BSD-3-Clause
tags
caffe, deep-learning, gpu, machine-learning, torch, html

âš™ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
other

📊 Engagement & Metrics

downloads
0
stars
4,181
forks
0

Data indexed from public sources. Updated daily.