Textbooks Are All You Need

Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno +14 more
6/20/2023
cs.CLcs.AIcs.LG

No official code found. Best implementation: kyegomez/phi-1 (73 stars, MIT, last commit 2023-09-18).

Abstract

We introduce phi-1, a new large language model for code, with significantly smaller size than competing models: phi-1 is a Transformer-based model with 1.3B parameters, trained for 4 days on 8 A100s, using a selection of ``textbook quality" data from the web (6B tokens) and synthetically generated textbooks and exercises with GPT-3.5 (1B tokens). Despite this small scale, phi-1 attains pass@1 accuracy 50.6% on HumanEval and 55.5% on MBPP. It also displays surprising emergent properties compared to phi-1-base, our model before our finetuning stage on a dataset of coding exercises, and phi-1-small, a smaller model with 350M parameters trained with the same pipeline as phi-1 that still achieves 45% on HumanEval.

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Code Implementations(1)

kyegomez/phi-1Community57%
MIT

Plug in and play implementation of " Textbooks Are All You Need", ready for training, inference, and dataset generation

738Python, DockerfileJun 21, 20233 years agoMIT

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Cite this paper

@article{gunasekar2023textbooks,
  title  = {Textbooks Are All You Need},
  author = {Suriya Gunasekar and Yi Zhang and Jyoti Aneja and Caio César Teodoro Mendes and Allie Del Giorno and Sivakanth Gopi and Mojan Javaheripi and Piero Kauffmann and Gustavo de Rosa and Olli Saarikivi and Adil Salim and Shital Shah and Harkirat Singh Behl and Xin Wang and Sébastien Bubeck and Ronen Eldan and Adam Tauman Kalai and Yin Tat Lee and Yuanzhi Li},
  year   = {2023},
  eprint = {2306.11644},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.11644v2}
}

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