You can deploy this model and start earning money today!

ssu-project/
OLMo-2-1124-7B-Instruct-ig-ssu_128

Name: OLMo-2-1124-7B-Instruct-ig-ssu_128
Availability: InStock

allenai/OLMo-2-1124-7B-Instruct

finetune

apache-2.0

Views

No views yet

OLMo 2 1124 7B Instruct for Igbo: SSU-Wanda (Calibration with 128 samples)

This model is built on top of OLMo 2 1124 7B Instruct adapted for Igbo using 200M target language tokens sampled from MADLAD-400. The model is adapted using the SSU-Wanda approach but calibrated with 128 samples instead of 500 samples.

Model Description

Language: Igbo
License: Apache 2.0
Fine-tuned from model: allenai/OLMo-2-1124-7B-Instruct

Model Sources

Repository: https://github.com/gucci-j/ssu
Paper: https://arxiv.org/abs/2512.04844

How to Get Started with the Model

Use the code below to get started with the model.

python

from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained(
    "ssu-project/OLMo-2-1124-7B-Instruct-ig-ssu_128"
)
tokenizer = AutoTokenizer.from_pretrained(
    "ssu-project/OLMo-2-1124-7B-Instruct-ig-ssu_128"
)

Citation

@misc{yamaguchi2025mitigatingcatastrophicforgettingtarget,
    title={Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates}, 
    author={Atsuki Yamaguchi and Terufumi Morishita and Aline Villavicencio and Nikolaos Aletras},
    year={2025},
    eprint={2512.04844},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2512.04844}, 
}