gplsi/Aitana-2B-S-IP-base

Aitana-2B-S-base-IP

Aitana-2B-S-base-IP is a generative language model from the Aitana family, developed by the GPLSI (Language and Information System Group) at the University of Alicante. This model is based on BSC-LT/salamandra-2b and has been further trained on Intellectual Property domain data.

Table of Contents

• Model Description
• Training Data
• Intended Uses
• How to Use
• Additional Information

Model description

Based on the files shipped in this repository, the checkpoint uses the Salamandra architecture and the Transformers ecosystem. The local configuration indicates:

Property	Value
Base Model	BSC-LT/salamandra-2b
Architecture	Transformer decoder-only
Context length	8192
Parameters	~2.25B
Languages	Spanish, English
License	Apache 2.0

Training

Training Data

This model was trained on the following IP domain dataset:

Dataset ID	Name	Language	Source
dc49	EURLEX	English	gplsi/alia_intellectual_property
dc49	EURLEX	Spanish	gplsi/alia_intellectual_property
dc50	COUNTERFEIT	English	gplsi/discriminative_counterfeit_en
dc50	COUNTERFEIT	Spanish	gplsi/discriminative_counterfeit_es

Training hyperparameters

TO-DO

Intended uses and limitations

This model can be used for:

• IP text generation in Spanish, and English
• Fine-tuning for specific IP downstream tasks

Note: This model is specifically optimized for IP domain content. For general-purpose or administrative/legal text, consider using other models in the Aitana family.

How to use

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "gplsi/Aitana-2B-S-base-IP"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

prompt = "Escriu un breu resum sobre la importància de la llengua."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs,
    max_new_tokens=128,
    do_sample=True,
    top_p=0.9,
    temperature=0.7,
    eos_token_id=tokenizer.eos_token_id,
    pad_token_id=tokenizer.pad_token_id,
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Evaluation

TO-DO

Additional Information

Author

The model has been developed by the Language and Information Systems Group (GPLSI) and the Centro de Inteligencia Digital (CENID), both part of the University of Alicante (UA), as part of their ongoing research in Natural Language Processing (NLP).

Funding

This work is funded by the Ministerio para la Transformación Digital y de la Función Pública, co-financed by the EU – NextGenerationEU, within the framework of the project Desarrollo de Modelos ALIA. This work has also been partially supported by Project HEART-NLP (PID2024-156263OB-C22).

Acknowledgments

We would like to express our gratitude to all individuals and institutions that have contributed to the development of this work.

Special thanks to:

• Language Technologies Laboratory at Barcelona Supercomputing Center
• Centro Vasco de Tecnología de la Lengua (HiTZ)
• Centro Singular de Investigación en Tecnologías Inteligentes (CiTIUS)
• Sistemas Inteligentes de Acceso a la Información (SINAI)
• Instituto Universitario de Investigación Informática (IUII)
• Leonardo HPC System
• European supercomputing ecosystem (EUROHPC)

We also acknowledge the financial, technical, and scientific support of the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project Desarrollo de Modelos ALIA, whose contribution has been essential to the completion of this research.

License

Apache License 2.0

Disclaimer

This model is intended for general purposes and is available under a permissive Apache License 2.0. Be aware that the model may have biases and/or undesirable outputs. Users deploying systems based on this model are responsible for mitigating risks and complying with applicable AI regulations.

Reference

@misc{gplsi-aitana-2B-S-base,
  author       = {Estevanell-Valladares, Ernesto L. and Sepúlveda-Torres, Robiert and Galeano, Santiago and Consuegra-Ayala, Juan Pablo and Miró Maestre, María and Martínez-Murillo, Iván and Grande, Eduardo and Canal-Esteve, Miquel and Bonora, Mar and Gutierrez, Yoan and Abreu Salas, José Ignacio and Lloret, Elena and Montoyo, Andrés and Muñoz-Guillena and Palomar, Manuel},
  title        = {Aitana-2B-S-base-IP: Continually pre-trained on Valencian},
  year         = {2025},
  institution  = {Language and Information Systems Group (GPLSI) and Centro de Inteligencia Digital (CENID), University of Alicante (UA)},
  howpublished = {\url{https://huggingface.co/gplsi/gplsi/Aitana-2B-S-base}},
  note         = {Accessed: 2026-05-12}
}

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Copyright © 2026 Language and Information Systems Group (GPLSI) and Centro de Inteligencia Digital (CENID), University of Alicante (UA). Distributed under the Apache License 2.0.