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DS4AI-UPB/qwen25-ro-re-lora
qwen25-ro-re-lora is a text generation model from DS4AI-UPB. Use it when you need the model to write or continue text. It is set up for peft. The card lists the license as apache-2.0.
Dragoș Mitruț Vasile · Elena-Simona Apostol · Stefan-Adrian Toma · Adrian Paschke · Ciprian-Octavian Truică
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From the Hugging Face model README
Dragoș Mitruț Vasile · Elena-Simona Apostol · Stefan-Adrian Toma · Adrian Paschke · Ciprian-Octavian Truică
QLoRA adapter for Qwen/Qwen2.5-32B-Instruct, fine-tuned for Relation Classification on a Romanian translation of SemEval-2010 Task 8 plus the original English data. Given a sentence with two marked entities (<e1>, <e2>), the model assigns one of ten directional relations.
| Language | F1-Score | Accuracy |
|---|---|---|
| English | 0.890 | 0.880 |
| Romanian | 0.864 | 0.853 |
Under zero-shot prompting this model scores far lower (0.320 English), but QLoRA fine-tuning brings it level with the best models: it is statistically indistinguishable from a fine-tuned XLM-RoBERTa-large (560M) on Romanian (paired bootstrap, p = 0.13), despite being roughly 57x larger.
Qwen/Qwen2.5-32B-Instruct, loaded in 4-bitfrom transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-32B-Instruct", load_in_4bit=True, device_map="auto")
model = PeftModel.from_pretrained(base, "DS4AI-UPB/qwen25-ro-re-lora")
tok = AutoTokenizer.from_pretrained("DS4AI-UPB/qwen25-ro-re-lora")
Prompt format and the full relation label set are in the run_inference.py script in the code repository.
The Romanian training data is machine-translated with automatic post-validation, not a human gold standard. See the paper and the code repository for the translation quality analysis.
@misc{vasile2026crosslingual,
title = {Cross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian},
author = {Vasile, Drago\c{s}-Mitru\c{t} and Apostol, Elena-Simona and Toma, \c{S}tefan-Adrian and Paschke, Adrian and Truic\u{a}, Ciprian-Octavian},
year = {2026},
note = {Preprint}
}