This is a fine-tuned version of the EuroLLM-9B-Instruct model, adapted for answering questions about legislation in Latvia. The model was fine-tuned on a dataset of ~15 thousand question–answer pairs sourced from the LVportals.lv archive.
Quantized versions of the model are available for use with Ollama or other local LLM runtime environments that support the GGUF format.
The data preparation, fine-tuning process, and comprehensive evaluation are described in more detail in:
Artis Pauniņš. Evaluation and Adaptation of Large Language Models for Question-Answering on Legislation. Master’s Thesis. University of Latvia, 2025.
Note:
The model may occasionally generate overly long responses. To prevent this, it is recommended to set the num_predict parameter to limit the number of tokens generated - either in your Python code or in the Modelfile, depending on how the model is run.