EuroLLM-2512

About

What EuroLLM-2512 is

Model Card for EuroLLM-9B-Instruct-2512 This is the model card for EuroLLM-9B-Instruct-2512, an improved version of utter-project/EuroLLM-9B-Instruct. In comparison with the previous version, this version includes the long-context extension phase and the revamped post-training recipe from utter-project/EuroLLM-22B-Instruct. - Developed by: Instituto Superior Técnico - University of Lisbon, Instituto de Telecomunicações, University of Edinburgh, Aveni, Unbabel, University of Paris-Saclay, Artefact Research Center, University of Amsterdam, Naver Labs, Sorbonne Université. - Funded by: European Union. - Model type: A 9B parameter multilingual transfomer LLM. - Language(s) (NLP): Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Hungarian, Irish, Italian, Latvian, Lithuanian, Maltese, Polish, Portuguese, Romanian, Slovak, Slovenian, Spanish, Swedish, Arabic, Catalan, Chinese, Galician, Hindi, Japanese, Korean, Norwegian, Russian, Turkish, and Ukrainian. - License: Apache License 2.0. <img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/ axolotl version: 0.12.2 Run the model from transformers import AutoModelForCausalLM, AutoTokenizer modelid = "utter-project/EuroLLM-9B-Instruct-2512" tokenizer = AutoTokenizer.frompretrained(modelid) model = AutoModelForCausalLM.frompretrained(modelid) 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.applychattemplate(messages, tokenize=True, addgenerationprompt=True, returntensors="pt") outputs = model.generate(inputs, maxnewtokens=1024) print(tokenizer.decode(outputs[0], skipspecialtokens=True)) Bias, Risks, and Limitations EuroLLM-9B has not been aligned to human preferences, so the model may generate problematic outputs (e.g., hallucinations, harmful content, or false statements). Citation If you use our work, please cite:

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

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Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys eurollm-2512 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (eurollm-2512 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"eurollm-2512","messages":[{"role":"user","content":"Hello"}]}'

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