---
base_model: unsloth/Qwen3-1.7B-unsloth-bnb-4bit
license: mit
pipeline_tag: text-generation
tags:
- base_model:adapter:unsloth/Qwen3-1.7B-unsloth-bnb-4bit
- lora
- sft
- transformers
- trl
- unsloth
- citation-preprocessing
- text-refinement
- academic-text-processing
inference:
  parameters:
    temperature: 0.6
    top_p: 0.95
    max_new_tokens: 512
ollama:
  parameters:
    num_ctx: 1024
    temperature: 0.6
    top_p: 0.95
---

# SemanticCite-Refiner-Qwen3-1B

A fine-tuned Qwen3-1.7B model specialized for preprocessing citation text. This model removes reference markers, author names, and publication identifiers while converting author-centered statements to fact-centered statements for improved citation verification.

## Model Details

### Model Description

This model is designed to preprocess citation text by cleaning and standardizing it for downstream verification tasks. It removes reference markers (e.g., [1], Smith 2020, et al.), converts author-centered statements to fact-centered statements using passive voice, while maintaining all numerical values and factual details.

- **Developed by:** Sebastian Haan
- **Model type:** Causal Language Model (Fine-tuned)
- **Language(s) (NLP):** English
- **License:** MIT
- **Finetuned from model:** unsloth/Qwen3-1.7B-unsloth-bnb-4bit


## Uses

### Direct Use

This model is intended for:
- Preprocessing citation text for academic verification systems
- Cleaning and standardizing citation statements
- Converting author-centric to fact-centric statements
- First stage in citation verification pipelines


### Out-of-Scope Use

This model should not be used for:
- General text summarization or rewriting
- Legal document processing
- Medical text processing
- Creative writing or content generation