ServiceNow, Hugging Face & Nvidia Announce Gen AI Code Tools

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The companies say StarCoder2 advances code generation, transparency, governance and innovation
ServiceNow, Hugging Face and Nvidia announce StarCoder2, a family of open‑access LLMs for code generation, aimed at helping build enterprise applications

ServiceNow, Hugging Face and Nvidia have announced the release of StarCoder2, a family of open‑access large language models (LLMs) for code generation, aimed at helping build enterprise applications. 

StarCoder2 was developed by the BigCode community, stewarded by digital workflow company ServiceNow and open‑source platform Hugging Face. Trained on 619 programming languages, the companies say StarCoder2 can be further trained and embedded in enterprise applications to perform specialised tasks such as application source code generation, workflow generation, text summarisation and more. 

Transforming the world today, generative AI (Gen AI) tools are being used in a number of ways, with companies such as BT Group benefitting from AI coding tools. StarCoder2 offers three model sizes: a three billion‑parameter model trained by ServiceNow, a seven billion‑parameter model trained by Hugging Face, and a 15 billion‑parameter model built by Nvidia and trained on its accelerated infrastructure. The smaller variants provide powerful performance while saving on compute costs, with the new StarCoder2 three billion‑parameter model reportedly matching the performance of the original StarCoder 15 billion‑parameter model.

“StarCoder2 stands as a testament to the combined power of open scientific collaboration and responsible AI practices with an ethical data supply chain,” comments Harm de Vries, lead of ServiceNow's StarCoder2 development team, and co‑lead of BigCode. "The state‑of‑the‑art open‑access model improves on prior generative AI performance to increase developer productivity and provides developers equal access to the benefits of code generation AI, which in turn enables organisations of any size to more easily meet their full business potential.”

AI model prioritises transparency and open governance

StarCoder2 models share a state‑of‑the‑art architecture and carefully curated data sources from BigCode that prioritise transparency and open governance to enable responsible innovation at scale.  

The foundation of StarCoder2 is a new code dataset called The Stack v2 which is more than 7x larger than The Stack v1. In addition to the advanced data set, new training techniques help the model understand low‑resource programming languages (such as COBOL), mathematics, and program source code discussions.

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StarCoder2 advances the potential of future AI‑driven coding applications, including text‑to‑code and text‑to‑workflow capabilities. With broader, deeper programming training, it provides repository context, enabling accurate, context‑aware predictions. These advancements serve seasoned software engineers and citizen developers alike, accelerating business value and digital transformation.

“The joint efforts led by Hugging Face, ServiceNow and Nvidia enable the release of powerful base models that empower the community to build a wide range of applications more efficiently with full data and training transparency,” explains Leandro von Werra, Machine Learning Engineer at Hugging Face and co‑lead of BigCode. “StarCoder2 is a testament to the potential of open‑source and open science as we work toward democratising responsible AI.” 

All StarCoder2 models will also be available for download from Hugging Face and the StarCoder2 15B model is available on Nvidia AI Foundation models for developers to experiment with directly from their browser, or through an API endpoint.

“Since every software ecosystem has a proprietary programming language, code LLMs can drive breakthroughs in efficiency and innovation in every industry,” says Jonathan Cohen, Vice President of Applied Research at Nvidia. “Nvidia’s collaboration with ServiceNow and Hugging Face introduces secure, responsibly developed models, and supports broader access to accountable generative AI that we hope will benefit the global community.”

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