---
language:
- cs
license: apache-2.0
library_name: transformers
base_model:
- allenai/Olmo-3-1025-7B
tags:
- multilingual
- synthetic
- sft
datasets:
- ljvmiranda921/PolyglotTeachers-SFT-Synth
---

<img alt="Logo for LTL" src="ltl_logo2.svg" width="240px" style="margin-left:'auto' margin-right:'auto' display:'block'">

# Polyglot-OLMo3-7B-SFT-cs

This model is a fine-tuned version of [allenai/OLMo-3-1025-7B](https://huggingface.co/allenai/OLMo-3-1025-7B) on Czech synthetic data, using the best teacher-student combination identified in our paper [Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation]().

The training data was generated by [google/gemma-3-27b-it](https://huggingface.co/google/gemma-3-27b-it) and is available in the [PolyglotTeachers-SFT-Synth](https://huggingface.co/datasets/ljvmiranda921/PolyglotTeachers-SFT-Synth) dataset.

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "ljvmiranda921/Polyglot-OLMo3-7B-SFT-cs"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

messages = [{"role": "user", "content": "Ahoj, jak se máš?"}]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
outputs = model.generate(inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## Acknowledgements

LJVM and AK acknowledge the support of the UKRI Frontier Grant EP/Y031350/1 ([EQUATE](https://gtr.ukri.org/projects?ref=EP%2FY031350%2F1)).
This work was performed using joint resources provided by the [Cambridge Service for Data Driven Discovery (CSD3)](https://hpc.cam.ac.uk/high-performance-computing) EP/T022159/1 and the [Isambard AI National AI Research Resource (AIRR)](https://www.bristol.ac.uk/research/centres/bristol-supercomputing/#isambard-ai) ST/AIRR/I-A-I/1023, and the Microsoft Research Grant.
LJVM would also like to thank Songbo Hu, Chen Cecilia Liu, Millicent Ochieng, and Felermino Ali for helpful and productive discussions on the project.

## Citation

```bibtex
@misc{miranda2026polyglotteachersevaluatinglanguage,
      title={Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation}, 
      author={Lester James V. Miranda and Ivan Vulić and Anna Korhonen},
      year={2026},
      eprint={2604.11290},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2604.11290}, 
}
```