base_model, license, pipeline_tag, tags, inference, ollama

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