Instructions to use noystl/llama-8b-e2e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noystl/llama-8b-e2e with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("noystl/llama-8b-e2e", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card with metadata and description
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README.md
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```bibtex
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@misc{sternlicht2025chimeraknowledgebaseidea,
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---
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license: mit
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library_name: transformers
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pipeline_tag: text-generation
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---
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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](https://huggingface.co/papers/2505.20779). The model utilizes a LoRA adapter on top of a Mistral base model.
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Project page: https://noy-sternlicht.github.io/CHIMERA-Web
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Code: https://github.cs.huji.ac.il/tomhope-lab/CHIMERA
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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.
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```bibtex
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@misc{sternlicht2025chimeraknowledgebaseidea,
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