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Computer Science > Computation and Language

arXiv:2406.11409 (cs)
[Submitted on 17 Jun 2024 (v1), last revised 19 Jun 2024 (this version, v2)]

Title:CodeGemma: Open Code Models Based on Gemma

Authors:CodeGemma Team: Heri Zhao, Jeffrey Hui, Joshua Howland, Nam Nguyen, Siqi Zuo, Andrea Hu, Christopher A. Choquette-Choo, Jingyue Shen, Joe Kelley, Kshitij Bansal, Luke Vilnis, Mateo Wirth, Paul Michel, Peter Choy, Pratik Joshi, Ravin Kumar, Sarmad Hashmi, Shubham Agrawal, Zhitao Gong, Jane Fine, Tris Warkentin, Ale Jakse Hartman, Bin Ni, Kathy Korevec, Kelly Schaefer, Scott Huffman
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Abstract:This paper introduces CodeGemma, a collection of specialized open code models built on top of Gemma, capable of a variety of code and natural language generation tasks. We release three model variants. CodeGemma 7B pretrained (PT) and instruction-tuned (IT) variants have remarkably resilient natural language understanding, excel in mathematical reasoning, and match code capabilities of other open models. CodeGemma 2B is a state-of-the-art code completion model designed for fast code infilling and open-ended generation in latency-sensitive settings.
Comments: v1: 11 pages, 4 figures, 5 tables. v2: Update metadata
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2406.11409 [cs.CL]
  (or arXiv:2406.11409v2 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2406.11409

Submission history

From: Nam Nguyen [view email]
[v1] Mon, 17 Jun 2024 10:54:35 UTC (64 KB)
[v2] Wed, 19 Jun 2024 02:37:50 UTC (64 KB)
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