Textbooks Are All You Need - Gunasekar, Suriya; Zhang, Yi; Aneja, Jyoti; Cesar, Caio; Mendes, Teodoro; Giorno, Allie Del; Gopi, Sivakanth; Javaheripi, Mojan; Kauffmann, Piero; de Rosa, Gustavo; Saarikivi, Olli; Salim, Adil; et al. (2023)
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.