Edward Beeching
Hugging Face research scientist; credited author of the TRL library and co-first author of Zephyr
- Machine Learning Research Scientist, Hugging Face12
Edward Beeching is a Machine Learning Research Scientist at Hugging Face, where Beeching's recent work covers reinforcement learning and post-training for language models, open reasoning systems, and efficient training infrastructure. Beeching is one of the authors credited in the citation file of TRL, Hugging Face's open-source post-training library, and co-first author of the Zephyr paper on distilling alignment into a smaller open chat model. Beeching also co-authored Hugging Face blog posts on TRL, including a 2023 guide to fine-tuning a 20B model with RLHF on a 24GB consumer GPU, and is listed among the authors of the SmolLM3 release.12354
Work
TRL (Transformers Reinforcement Learning)Open-source code
Listed among the authors in TRL's CITATION.cff, which describes the Apache-2.0 library as an open-source toolkit for post-training with SFT, reward modeling, DPO, and GRPO. Beeching's site also lists co-authored Hugging Face blog posts on TRL, such as "Fine-Tuning 20B LLMs with RLHF on a 24GB Consumer GPU" (2023) and a 2026 post on delta weight sync in TRL.31
SmolLM3Open weights
Listed among the authors of the Hugging Face blog post and citation for SmolLM3, which the post describes as a fully open 3B multilingual, long-context reasoning model released with its checkpoint and full training recipe.41
Zephyr: Direct Distillation of LM Alignment (external site: arxiv.org)Published research
Co-first author with Lewis Tunstall of the 2023 paper, which applies distilled direct preference optimization with AI feedback to align a smaller open language model to user intent.51
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