noystl/Recombination-Extraction
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How to use noystl/mistral_abstract_classifier with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("feature-extraction", model="noystl/mistral_abstract_classifier") # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("noystl/mistral_abstract_classifier", dtype="auto")This Hugging Face repository hosts a fine-tuned Mistral model designed to classify scientific abstracts based on whether they involve idea recombination, as introduced in the paper CHIMERA: A Knowledge Base of Idea Recombination in Scientific Literature. The model employs a LoRA adapter on top of a Mistral base model.
For detailed usage instructions and to reproduce the results, please refer to the linked GitHub repository.
Bibtex
@misc{sternlicht2025chimeraknowledgebaseidea,
title={CHIMERA: A Knowledge Base of Idea Recombination in Scientific Literature},
author={Noy Sternlicht and Tom Hope},
year={2025},
eprint={2505.20779},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2505.20779},
}
Quick Links
Base model
mistralai/Mistral-7B-v0.3