CHIMERA: Extraction models
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7 items • Updated
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("noystl/mistral-e2e", dtype="auto")Quick Links
This Hugging Face repository contains a fine-tuned Mistral model trained for the task of extracting recombination examples from scientific abstracts, as described in the paper CHIMERA: A Knowledge Base of Idea Recombination in Scientific Literature. The model utilizes a LoRA adapter on top of a Mistral base model. The model can be used for the information extraction task of identifying recombination examples within scientific text. For detailed usage instructions and reproduction of results, please refer to the Github repository linked above.
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},
}
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Model tree for noystl/mistral-e2e
Base model
mistralai/Mistral-7B-v0.3 Finetuned
mistralai/Mistral-7B-Instruct-v0.3
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="noystl/mistral-e2e")