huggingface/autotrain-advanced

🤗 AutoTrain Advanced

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Summary Information

Updated 16 minutes ago
Added to GitGenius on September 15th, 2026
Created on December 15th, 2020
Open Issues & Pull Requests: 1 (+0)
GitHub issues: Enabled
Number of forks: 627
Total Stargazers: 4,612 (+0)
Total Subscribers: 74 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 4.6 hours
Mean response time: 7.6 days
90th percentile: 30.2 days
Tracked items: 104

Most active contributors

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How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 13% of issues opened in the past year have been closed. Three people close 50% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 1
New in 7 days: 0
Closed in 7 days: 1
Avg open age: 26 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 1
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • stale (149)
  • bug (73)
  • feature request (18)

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Detailed Description

AutoTrain Advanced is a no-code machine learning training platform that simplifies model training and deployment through a web interface.

The tool addresses the complexity of setting up machine learning pipelines by automating the training process for state-of-the-art models. Users upload data in the correct format and configure training through a graphical interface without writing code. The platform handles model selection, hyperparameter configuration, and deployment, abstracting away the technical details typically required for machine learning workflows.

Developers considering adoption should be aware that this project is no longer maintained. The README explicitly states that no new features will be added and bugs will not be fixed. The maintainers recommend using Axolotl, TRL, or transformers.Trainer as alternatives. The tool remains free to use, with costs only incurred for computational resources when running on Hugging Face Spaces or on personal infrastructure. It is best suited for users who prioritize ease of use over customization and who want to avoid writing training code entirely.

The project shows minimal development activity with no ongoing maintenance or bug fixes being applied.