ServiceNow (NYSE: NOW), Hugging Face, and NVIDIA today announced the release of StarCoder2, a family of open-access large language models for code generation that sets new standards for performance, transparency, and cost-effectiveness.

StarCoder2 was developed in partnership with the BigCode Community, managed by ServiceNowthe leading digital workflow company making the world work better for everyone, and Hugging Facethe most-used open-source platform, where the machine learning community collaborates on models, datasets, and applications.

Trained on 619 programming languages, StarCoder2 can be further trained and embedded in enterprise applications to perform specialized tasks such as application source code generation, workflow generation, text summarization, and more. Developers can use its code completion, advanced code summarization, code snippets retrieval, and other capabilities to accelerate innovation and improve productivity.

StarCoder2 offers three model sizes: a 3-billion-parameter model trained by ServiceNow; a 7-billion-parameter model trained by Hugging Face; and a 15-billion-parameter model built by NVIDIA with NVIDIA NeMo and trained on NVIDIA accelerated infrastructure. The smaller variants provide powerful performance while saving on computing costs, as fewer parameters require less computing during inference. In fact, the new 3-billion-parameter model matches 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,” emphasizes 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 organizations of any size to more easily meet their full business potential.”

“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,” said 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 democratizing responsible AI.”

“Since every software ecosystem has a proprietary programming language, code LLMs can drive breakthroughs in efficiency and innovation in every industry,” said 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 believe will benefit the global community.”

StarCoder2 Models Supercharge Custom Application Development

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

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

Fine-Tuning Advances Capabilities With Business-Specific Data

Users can fine-tune the open-access StarCoder2 models with industry- or organization-specific data using open-source tools such as NVIDIA NeMo or Hugging Face TRL. They can create advanced chatbots to handle more complex summarization or classification tasks, develop personalized coding assistants that can quickly and easily complete programming tasks, retrieve relevant code snippets, and enable text-to-workflow capabilities.

Organizations have already begun to fine-tune the foundational StarCoder model to create specialized task-specific capabilities for their businesses.

ServiceNow’s text-to-code Now LLM was purpose-built on a specialized version of the 15-billion-parameter StarCoder LLM, fine-tuned and trained for its workflow patterns, use cases, and processes. Hugging Face has also used the model to create its StarChat assistant.

BigCode Fosters Open Scientific Collaboration in AI

BigCode represents an open scientific collaboration led by Hugging Face and ServiceNow, dedicated to the responsible development of LLMs for code.

The BigCode community actively participates in the technical aspects of the StarCoder2 project through working groups and task forces, leveraging ServiceNow’s Fast LLM framework to train the 3-billion-parameter model, Hugging Face’s nanotron framework for the 7-billion-parameter model and the NVIDIA NeMo cloud-native framework and NVIDIA TensorRT-LLM software to train and optimize the 15-billion-parameter model.

Fostering responsible innovation is at the core of BigCode’s purpose, demonstrated through its open governance, transparent supply chain, use of open-source software, and the ability for developers to opt data out of training. StarCoder2 was built using responsibly sourced data under license from the digital commons of Heritage Softwarehosted by Inria.

“StarCoder2 is the first code generation AI model developed using the Software Heritage source code archive and built to align with our policies for responsible development of models for code,” stated Roberto Di Cosmo, director at Software Heritage. “The collaboration of ServiceNow, Hugging Face, and NVIDIA exemplifies a shared commitment to ethical AI development, advancing technology for the greater good.”

StarCoder2, like its predecessor, will be made available under the BigCode Open RAIL-M license, allowing royalty-free access and use. Further fostering transparency and collaboration, the model’s supporting code will continue to reside on the BigCode project’s GitHub page.

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

For more information on StarCoder2, visit https://huggingface.co/bigcode.

Let’s talk about the popular Constellation Software Inc. (TSE:CSU). The company’s shares saw a significant share price rise of 22% in the past couple of months on the TSX. The company’s trading levels have reached its highest for the past year, following the recent bounce in the share price. With many analysts covering the large-cap stock, we may expect any price-sensitive announcements to have already been factored into the stock’s share price. However, could the stock still be trading at a relatively cheap price? Let’s examine Constellation Software’s valuation and outlook in more detail to determine if there’s still a bargain opportunity.

View our latest analysis for Constellation Software

Is Constellation Software Still Cheap?

The stock seems fairly valued at the moment according to our valuation model. It’s trading around 15% below our intrinsic value, which means if you buy Constellation Software today, you’d be paying a fair price for it. And if you believe that the stock is really worth CA$4374.84, then there’s not much of an upside to gain from mispricing. In addition to this, Constellation Software has a low beta, which suggests its share price is less volatile than the wider market.

Can we expect growth from Constellation Software?

Future outlook is an important aspect when you’re looking at buying a stock, especially if you are an investor looking for growth in your portfolio. Buying a great company with a robust outlook at a cheap price is always a good investment, so let’s also take a look at the company’s future expectations. With profits expected to grow by 38% over the next couple of years, the future seems bright for Constellation Software. It looks like higher cash flow is on the cards for the stock, which should feed into a higher share valuation.

What This Means For You

Are you a shareholder? CSU’s optimistic future growth appears to have been factored into the current share price, with shares trading around its fair value. However, there are also other important factors which we have not considered today, such as the financial strength of the company. Have these factors changed since the last time you looked at the stock? Will you have enough confidence to invest in the company should the price drop below its fair value?

Are you a potential investor? If you’ve been keeping tabs on CSU, now may not be the most optimal time to buy, given it is trading around its fair value. However, the optimistic prospect is encouraging for the company, which means it’s worth diving deeper into other factors such as the strength of its balance sheet, in order to take advantage of the next price drop.

Story continues

If you want to dive deeper into Constellation Software, you’d also look into what risks it is currently facing. For example, we’ve discovered 1 warning sign that you should run your eyes over to get a better picture of Constellation Software.

If you are no longer interested in Constellation Software, you can use our free platform to see our list of over 50 other stocks with a high growth potential.

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This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.