Fill-Mask
Transformers
Safetensors
Luxembourgish
modernbert
encoder
luxembourgish
multilingual
masked-language-modeling
Instructions to use instilux/ltz-e1-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use instilux/ltz-e1-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="instilux/ltz-e1-mini")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("instilux/ltz-e1-mini") model = AutoModelForMaskedLM.from_pretrained("instilux/ltz-e1-mini") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## Citation
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## Citation
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Please cite this paper (preprint, accepted to ACL 2026 Findings) if you use this model in your work.
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@misc{plum2026ltzglueluxembourgishgenerallanguage,
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title={ltzGLUE: Luxembourgish General Language Understanding Evaluation},
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author={Alistair Plum and Felicia Körner and Anne-Marie Lutgen and Laura Bernardy and Fred Philippy and Emilia Milano and Nils Rehlinger and Cédric Lothritz and Tharindu Ranasinghe and Barbara Plank and Christoph Purschke},
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year={2026},
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eprint={2604.17976},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2604.17976},
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}
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