Text Generation
PEFT
Safetensors
English
lora
data-to-text
text-to-data
factual-consistency
hallucination-detection
Instructions to use Loria-MosAIk/xqdt-e2e-qwen3-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Loria-MosAIk/xqdt-e2e-qwen3-14b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B") model = PeftModel.from_pretrained(base_model, "Loria-MosAIk/xqdt-e2e-qwen3-14b") - Notebooks
- Google Colab
- Kaggle
Link XQDT paper in model card
Browse files
README.md
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## Citation
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```bibtex
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@inproceedings{efimov-zhang-etal-2026-xqdt,
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title = {XQDT: eXplainable and Quantitative Data-Text Alignment Metric with Feedback Signals},
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## Citation
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Paper: [Hugging Face](https://huggingface.co/papers/2608.29948) | [arXiv](https://arxiv.org/abs/2608.29948).
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```bibtex
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@inproceedings{efimov-zhang-etal-2026-xqdt,
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title = {XQDT: eXplainable and Quantitative Data-Text Alignment Metric with Feedback Signals},
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