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Textbooks Are All You Need

About

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.

Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio C\'esar Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, S\'ebastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li• 2023

Related benchmarks

TaskDatasetResultRank
Code SummarizationCodeXGLUE
Java Score14.6
38
Boundary DetectionRoFT-chatgpt GPT-3.5-turbo generated (test)
Accuracy36.5
34
Boundary DetectionRoFT original (test)
Accuracy20.9
27
Code TranslationCodefuseEval
Ja2Py Score73.8
21
Multi-task Code Intelligence (Overall)CodefuseEval and CodeXGLUE
Overall Score41.4
21
Code RepairCodeXGLUE
Repair Rate10.1
21
Clone DetectionCodeXGLUE
Clone Score93.5
21
Defect DetectionCodeXGLUE
Defect Rate0.611
21
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Other info

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