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| title: README | |
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| # Welcome to ServiceNow\'s page on HuggingFace! | |
| ServiceNow® is the AI platform for business transformation. We bring | |
| intelligence to every corner of your business by offering a single, | |
| cloud-based platform that combines AI, data, and workflows to help | |
| enterprises automate and manage critical processes across IT, HR, | |
| security, and more. For more information on our company and its | |
| products, visit our corporate website: [ServiceNow - Put AI to | |
| Work](https://www.servicenow.com/). | |
| On this site here, you will find open-source publications, including work from our | |
| fundamental [AI research team](https://www.servicenow.com/research/). | |
| You can also find more open-source publications on our [GitHub | |
| organization](https://github.com/Servicenow). | |
| Discover below a few of the projects we're especially proud to showcase. | |
| ## Benchmarks | |
| [BigDocsBench](https://huggingface.co/datasets/ServiceNow/BigDocs-Bench) | |
| is a benchmark designed to evaluate VLM document understanding at scale. | |
| [BrowserGym | |
| Leaderboard](https://huggingface.co/spaces/ServiceNow/browsergym-leaderboard) | |
| was created to evaluate LLMs, VLMs, and agents on web navigation tasks. | |
| [UI-Vision,](https://huggingface.co/datasets/ServiceNow/ui-vision) a | |
| benchmark for GUI visual grounding. | |
| ## Models | |
| [BigCode](https://www.bigcode-project.org/) is an open scientific | |
| collaboration focused on the responsible development of LLM for code. It | |
| addresses the lack of transparency in LLM development by promoting open | |
| governance, open datasets, and collaborative research. | |
| [StarCoder](https://huggingface.co/blog/starcoder) is a | |
| state-of-the-art, 15 B-parameter open-source language model for code, | |
| trained on 1 trillion tokens extracted from GitHub repositories spanning | |
| over 80 programming languages, and it achieves top performance on | |
| benchmarks like HumanEval---surpassing both open and closed-source | |
| alternatives---while offering an extensive 8K+ context window and | |
| enhanced safety features like PII redaction and attribution tracing. | |
| [Apriel-Nemotron-15b-Thinker,](https://huggingface.co/ServiceNow-AI/Apriel-Nemotron-15b-Thinker) | |
| a 15B-parameter reasoning model in ServiceNow's Apriel SLM series, | |
| delivering state-of-the-art performance on both enterprise and academic | |
| benchmarks while using only half the memory of larger models. | |
| [StarVector,](https://huggingface.co/starvector/starvector-8b-im2svg) a | |
| code-driven image generation framework. | |
| [AlignVLM,](https://huggingface.co/papers/2502.01341) a VLM that adapts | |
| visual features for large language models | |
| # Datasets | |
| [The Stack v2](https://huggingface.co/datasets/bigcode/the-stack-v2) is | |
| the largest open-access pretraining dataset for code-focused | |
| LLMs---featuring 67.5 TB (≈900 billion tokens) of meticulously curated, | |
| deduplicated, and cleaned source code---enabling next-gen models like | |
| StarCoder2 to train effectively at scale. | |
| [Repliqa](https://huggingface.co/datasets/ServiceNow/repliqa) is a | |
| human-curated evaluation dataset designed to test how well LLMs use | |
| contextual information from provided documents. It contains | |
| context--question--answer triplets based on realistic but fictional | |
| documents about invented people, places, and events---removing the | |
| chance for models to rely on memorized facts. |