Blog posts and white papers spanning tech & AI research, business & market trends, startup ecosystems, and the mission of de-risking, democratizing, and decentralizing AI.
A collaborative white paper co-published with the Toronto Machine Learning community, drawing on the real voices and experiences of women in data and AI to chart a path toward a more equitable future.
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Introducing Arcee-Meraj, a specialized Arabic large language model that demonstrates the power and importance of building high-quality LLMs for non-English languages and underrepresented communities.
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Introducing DistillKit, Arcee Labs' open-source toolkit for knowledge distillation of large language models — detailing the technical approach, architecture, and benchmarks behind the v0.1 release.
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A practical guide to data preparation for LLM training — covering collection, cleaning, formatting, and quality filtering to ensure your model learns effectively from your domain-specific corpus.
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An in-depth look at the non-obvious obstacles that arise when adapting general-purpose large language models to specialized domains, and how to navigate them effectively.
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How Arcee's continual pre-training and model merging techniques, combined with AWS Trainium chips, accelerate LLM domain adaptation for medical, legal, and financial verticals — while reducing costs and enforcing compliance.
Read on AWS Blog
A deep-dive case study exploring how continual pre-training and model merging techniques can be combined to achieve effective domain adaptation in large language models.
Read on Arcee Blog