65 lines
1.7 KiB
Markdown
65 lines
1.7 KiB
Markdown
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---
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base_model: unsloth/Qwen3-1.7B-unsloth-bnb-4bit
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license: mit
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pipeline_tag: text-generation
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tags:
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- base_model:adapter:unsloth/Qwen3-1.7B-unsloth-bnb-4bit
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- lora
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- sft
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- transformers
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- trl
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- unsloth
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- citation-preprocessing
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- text-refinement
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- academic-text-processing
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inference:
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parameters:
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temperature: 0.6
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top_p: 0.95
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max_new_tokens: 512
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ollama:
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parameters:
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num_ctx: 1024
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temperature: 0.6
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top_p: 0.95
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---
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# SemanticCite-Refiner-Qwen3-1B
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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.
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## Model Details
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### Model Description
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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.
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- **Developed by:** Sebastian Haan
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- **Model type:** Causal Language Model (Fine-tuned)
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- **Language(s) (NLP):** English
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- **License:** MIT
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- **Finetuned from model:** unsloth/Qwen3-1.7B-unsloth-bnb-4bit
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## Uses
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### Direct Use
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This model is intended for:
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- Preprocessing citation text for academic verification systems
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- Cleaning and standardizing citation statements
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- Converting author-centric to fact-centric statements
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- First stage in citation verification pipelines
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### Out-of-Scope Use
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This model should not be used for:
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- General text summarization or rewriting
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- Legal document processing
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- Medical text processing
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- Creative writing or content generation
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