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Stella Biderman

Executive Director, EleutherAI

Stella Biderman is the Executive Director of EleutherAI. Biderman is first author of the Pythia paper, which introduced 16 language models from 70M to 12B parameters, all trained on public data in the same order, with 154 checkpoints released for each model so researchers can study how models change over training and scale. Biderman is also among the credited authors of the Language Model Evaluation Harness, EleutherAI's open framework for evaluating language models.1234

At a glance

Current role
Executive Director
Company
EleutherAI
Sector
Nonprofit
Work listed
5
Sources cited
8
Profile reviewed

Open-source work

Biderman leads EleutherAI, whose staff page describes researchers, engineers, and operators supporting open AI science across open models and infrastructure, evaluation, multilingual NLP, and AI for science. Biderman was the second author of The Pile, an 800GB dataset of diverse English text for language modeling posted at the end of 2020, and of the 2022 paper describing GPT-NeoX-20B, an open-source autoregressive language model.156

In 2023 Biderman was first author of the paper on the Pythia suite, built to let researchers study how language models change across training and scale. More recently Biderman co-authored the Common Pile v0.1, an 8TB dataset of public domain and openly licensed text, in 2025.237

Evaluation

Biderman is among the credited authors of the Language Model Evaluation Harness and first author of Lessons from the Trenches on Reproducible Evaluation of Language Models (2024), which draws on experience maintaining that framework to discuss reproducible evaluation practice.48

Work and contributions

  • Pythia

    First author of the Pythia paper and first-listed author in the repository's citation for the model suite.23

  • LM Evaluation Harness

    Listed among the authors in the project's citation entry for the evaluation framework.4

  • The Pile Open data

    Second author, after Leo Gao, of the 2020 paper introducing The Pile, an 800GB dataset of diverse text for language modeling.5

  • GPT-NeoX-20B Open weights

    Second author, after Sid Black, of the 2022 paper describing GPT-NeoX-20B, an open-source autoregressive language model.6

  • Pythia 12B Open weights

    First author of the Pythia paper, which the Pythia 12B model card cites.2

Timeline

  1. Co-authored The Pile, an 800GB dataset of diverse text for language modeling.5
  2. Co-authored GPT-NeoX-20B: An Open-Source Autoregressive Language Model.6
  3. Posted the Pythia paper as first author, introducing a suite of models for studying training and scaling.2
  4. Posted Lessons from the Trenches on Reproducible Evaluation of Language Models as first author.8
  5. Co-authored The Common Pile v0.1, a dataset of public domain and openly licensed text.7

Where they work

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References

8 sources · profile reviewed Oct 21, 2026 · data updated Oct 22, 2026

  1. Staff — EleutherAIEleutherAI · Official page · accessed Oct 21, 2026
  2. Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling (arXiv 2304.01373)arXiv · Paper · published Apr 3, 2023 · accessed Oct 21, 2026
  3. EleutherAI/pythia (GitHub repository README)EleutherAI · Repository · accessed Oct 21, 2026
  4. EleutherAI/lm-evaluation-harness (GitHub repository README and CITATION.bib)EleutherAI · Repository · accessed Oct 21, 2026
  5. The Pile: An 800GB Dataset of Diverse Text for Language Modeling (arXiv 2101.00027)arXiv · Paper · published Dec 31, 2020 · accessed Oct 21, 2026
  6. GPT-NeoX-20B: An Open-Source Autoregressive Language Model (arXiv 2204.06745)arXiv · Paper · published Apr 14, 2022 · accessed Oct 21, 2026
  7. The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text (arXiv 2506.05209)arXiv · Paper · published Jun 5, 2025 · accessed Oct 21, 2026
  8. Lessons from the Trenches on Reproducible Evaluation of Language Models (arXiv 2405.14782)arXiv · Paper · published May 23, 2024 · accessed Oct 21, 2026