--- library_name: transformers license: other license_name: mixed pipeline_tag: text-generation language: - ar - es - cs - de - id - tl - ja base_model: - allenai/Olmo-3-1025-7B - google/gemma-3-4b-pt datasets: - ljvmiranda921/PolyglotTeachers-SFT-Synth tags: - multilingual - synthetic - sft ---
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# Multilingual Instruct Models (Polyglot Teachers) These are per-language models supervised fine-tuned on the synthetic data generated in the [Polyglot Teachers](https://huggingface.co/papers/2604.11290) project (see [ljvmiranda921/PolyglotTeachers-SFT-Synth](https://huggingface.co/datasets/ljvmiranda921/PolyglotTeachers-SFT-Synth)). Load a specific model by passing the branch as the `revision`: ```python from transformers import AutoModelForCausalLM, AutoTokenizer repo = "ljvmiranda921/Polyglot-SFT-Multilingual" branch = "Polyglot-OLMo3-7B-SFT-ar" # pick any branch below model = AutoModelForCausalLM.from_pretrained(repo, revision=branch) tokenizer = AutoTokenizer.from_pretrained(repo, revision=branch) ``` ## Branches | Branch | Description | | --- | --- | | `Polyglot-Gemma3-4B-SFT-ar` | Gemma-3 4B SFT — Arabic | | `Polyglot-Gemma3-4B-SFT-de` | Gemma-3 4B SFT — German | | `Polyglot-Gemma3-4B-SFT-id` | Gemma-3 4B SFT — Indonesian | | `Polyglot-Gemma3-4B-SFT-tl` | Gemma-3 4B SFT — Tagalog | | `Polyglot-OLMo3-7B-SFT-ar` | OLMo-3 7B SFT — Arabic | | `Polyglot-OLMo3-7B-SFT-cs` | OLMo-3 7B SFT — Czech | | `Polyglot-OLMo3-7B-SFT-de` | OLMo-3 7B SFT — German | | `Polyglot-OLMo3-7B-SFT-es` | OLMo-3 7B SFT — Spanish | | `Polyglot-OLMo3-7B-SFT-id` | OLMo-3 7B SFT — Indonesian | | `Polyglot-OLMo3-7B-SFT-ja` | OLMo-3 7B SFT — Japanese | ## Licensing This repo holds models under different licenses; each branch follows its base model's license: - `Polyglot-OLMo3-7B-SFT-*` (base [allenai/Olmo-3-1025-7B](https://huggingface.co/allenai/Olmo-3-1025-7B)) — Apache-2.0 - `Polyglot-Gemma3-4B-SFT-*` (base [google/gemma-3-4b-pt](https://huggingface.co/google/gemma-3-4b-pt)) — [Gemma license](https://ai.google.dev/gemma/terms) ## 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}, } ```