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noystl
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mistral-abstract-cot-classifier

Feature Extraction
Transformers
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How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("feature-extraction", model="noystl/mistral-abstract-cot-classifier")
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("noystl/mistral-abstract-cot-classifier", dtype="auto")
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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}, 
}

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