# huggingface/autotrain-advanced

🤗 AutoTrain Advanced

Repository: https://github.com/huggingface/autotrain-advanced
Canonical: https://ross.abutalabs.com/products/autotrain-advanced
Homepage: https://huggingface.co/autotrain
Language: Python
License: Apache-2.0
License Family: permissive
Topics: huggingface, deep-learning, machine-learning, natural-language-processing, natural-language-understanding, autotrain, python
Last push: 2026-07-21T09:55:09+00:00

## Health v2 (maintenance only)
Score: 74/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 93, release rhythm 35, longevity 100
- inputs: {"age_days": 2087, "days_push": 43, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4608, forks 628 (observed 2026-08-28T04:08:54.945534+00:00)

## What it is
AutoTrain Advanced is Hugging Face's no-code tool for training and deploying state-of-the-art machine learning models, covering LLM finetuning (SFT, DPO, ORPO), text/image classification, token classification, translation, summarization, and tabular tasks. It can run locally via CLI or on Hugging Face Spaces, paying only for compute used.

## Use cases
- finetune an LLM with SFT, DPO, or ORPO without writing training code
- train a text classification model from a CSV upload
- train an image classifier without ML expertise
- run AutoML training on my own GPU infrastructure
- train a tabular data regression model in a few clicks
- prepare and deploy finetuned models to the Hugging Face Hub

## When to choose
- you want no-code or low-config model training integrated with the Hugging Face ecosystem
- you need quick LLM finetuning experiments with YAML configs or notebooks
- you prefer paying only for compute on Spaces or your own hardware

## When to avoid
- you need maintained software with bug fixes or new features - the project is officially unmaintained
- you want cutting-edge finetuning - use Axolotl, TRL, or transformers.Trainer instead
- you need full programmatic control over training loops and hyperparameters

## Facets
- artifact type: application
- maturity: abandoned
- function: machine-learning, llm-training, nlp, cli, gui
- domain: machine-learning, deep-learning, large-language-models, computer-vision, data-science
- platform: python, cloud, self-hosted
- tags: no-code, automl, huggingface, llm-finetuning, sft, dpo, orpo, deprecated, natural-language-processing, docker

## Member repositories
- huggingface/autotrain-advanced (main) score 74

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:54.945534+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:19:44.280095+00:00, confidence not recorded.
  - readme: https://github.com/huggingface/autotrain-advanced (fetched 2026-08-28T04:08:54.945534+00:00, sha 3cf487138c5c)
  - homepage: https://huggingface.co/autotrain (fetched 2026-08-29T09:04:55.257218+00:00, sha ebad3881779b)
  - site_page: https://huggingface.co/docs (fetched 2026-08-29T09:04:55.266304+00:00, sha bdec26667b98)
  - site_page: https://huggingface.co/docs/autotrain/en/index (fetched 2026-08-29T09:04:55.270849+00:00, sha a23e9774f17f)
  - registry_pypi: https://pypi.org/pypi/autotrain-advanced/json (fetched 2026-08-29T09:04:55.276943+00:00, sha 31a964672261)
  - site_page: https://huggingface.co/pricing (fetched 2026-08-29T09:04:55.268194+00:00, sha de6b7a178be5)
  - site_page: https://huggingface.co/changelog (fetched 2026-08-29T09:04:55.272851+00:00, sha e045ccda5dfd)
  - site_page: https://huggingface.co/huggingface (fetched 2026-08-29T09:04:55.274549+00:00, sha 4acc88af409f)
- Data as of 2026-08-30T08:39:29.467469+00:00.