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utter-project/EuroLLM-9B-2512
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from transformers import AutoModelForCausalLM, AutoTokenizermodel_id = "utter-project/EuroLLM-9B-Instruct-2512"tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained(model_id)messages = [ { "role": "system", "content": "You are EuroLLM --- an AI assistant specialized in European languages that provides safe, educational and helpful answers.", }, { "role": "user", "content": "What is the capital of Portugal? How would you describe it?" }, ]inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")outputs = model.generate(inputs, max_new_tokens=1024)print(tokenizer.decode(outputs[0], skip_special_tokens=True))EuroLLM-9B has not been aligned to human preferences, so the model may generate problematic outputs (e.g., hallucinations, harmful content, or false statements).
If you use our work, please cite:
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@misc{ramos2026eurollm22btechnicalreport, title={EuroLLM-22B: Technical Report}, author={Miguel Moura Ramos and Duarte M. Alves and Hippolyte Gisserot-Boukhlef and João Alves and Pedro Henrique Martins and Patrick Fernandes and José Pombal and Nuno M. Guerreiro and Ricardo Rei and Nicolas Boizard and Amin Farajian and Mateusz Klimaszewski and José G. C. de Souza and Barry Haddow and François Yvon and Pierre Colombo and Alexandra Birch and André F. T. Martins}, year={2026}, eprint={2602.05879}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2602.05879}, }