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PLLuM is a family of large language models (LLMs) specialized in Polish with additional English data incorporated for broader generalization. Developed through an extensive collaboration with various data providers, PLLuM models are built on high-quality text corpora and refined through instruction tuning, preference learning, and advanced alignment techniques. These models are intended to generate contextually coherent text, offer assistance in various tasks (e.g., question answering, summarization), and serve as a foundation for specialized applications such as domain-specific intelligent assistants. In 2024, PLLuM models were developed by the PLLuM consortium. Since 2025, their development has continued under HIVE AI, a broader alliance of research institutions and organizations delivering digital public services, focused on open language technologies for Polish public administration. - **Extensive Data Collection** We gathered large-scale, high-quality text data in Polish and English, focusing on rigorous cleaning and deduplication to ensure the highest training standards. - **Organic Instruction Dataset** We curated the largest Polish collection of manually created “organic instructions”. This human-authored instruction set is based on an extensive typology of human-model interactions and it covers a range of subtle aspects of supervised fine-tuning (SFT) that might be overlooked with automated approaches (including large scale distillation of 'strong LLMs'). It was also designed to mitigate negative linguistic transfer from non-Polish textual data used in the pre-training phase.

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