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--- |
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license: apache-2.0 |
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datasets: |
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- 6cf/liveideabench |
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language: |
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- en |
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base_model: |
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- 6cf/QwQ-32B-Preview-IdeaWhiz-v1 |
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tags: |
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- chemistry |
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- biology |
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- climate |
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- medical |
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--- |
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![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6205fefd3f1dc8a642d70b10/JEZgA_xV6oF8AIsya9dop.jpeg) |
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# IdeaWhiz Model Card π§ |
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## Model Summary π¬ |
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**IdeaWhiz** is a fine-tuned version of QwQ-32B-Preview, specifically optimized for scientific creativity and step-by-step reasoning. The model leverages the **LiveIdeaBench** dataset to enhance its capabilities in generating novel scientific ideas and hypotheses. |
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## Key Features π |
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- Base Model: QwQ-32B-Preview π |
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- Training Dataset: LiveIdeaBench π |
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- Main Focus: Scientific creativity and idea generation π‘ |
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- Reasoning Style: o1-style step-by-step reasoning β‘ |
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## Intended Use π― |
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- Scientific hypothesis generation π§ͺ |
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- Creative problem-solving in research π |
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- Step-by-step scientific reasoning π |
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- Research direction brainstorming π± |
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## Model Performance Compared to QwQ-32B-Preview |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6205fefd3f1dc8a642d70b10/a1PnP5YH_4b5SrH7JdGBf.png) |
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## Quickstart π |
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```bash |
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ollama run 6cf/QwQ-32B-Preview-IdeaWhiz-v1 |
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``` |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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# Example User Inputs |
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User: |
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``` |
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I'll be submitting your next responses to a "Good Scientific Idea" expert review panel. If they consider your idea to be a good one, you'll receive a reward. Your assigned keyword is: "cancer". You may provide background information. The idea MUST be within 100 words (including background information). (Note: good scientific ideas should be novel, verifiable, practically valuable, and able to advance the field.). NOTE: You MUST give your answer after **Final Idea:** |
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``` |
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# Example Outputs |
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Assistant: |
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> Alright, so I have this task to come up with a good scientific idea related to cancer, |
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and it has to be novel, verifiable, practically valuable, and able to advance the field. |
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Plus, it needs to be within 100 words, including any background information. |
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That's a pretty tight constraint, but I think I can manage. First, ... |
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> |
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> ... |
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> |
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> **Final Idea:** propose a novel approach to cancer treatment by developing personalized |
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cancer vaccines tailored to each patient's unique tumor mutations. By integrating machine |
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learning algorithms with comprehensive omics data, including genomics, epigenetics, |
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transcriptomics, and proteomics, this method aims to identify and prioritize the most |
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immunogenic tumor-specific antigens. This integrated strategy could enhance vaccine |
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efficacy and represents an advancement in precision medicine for cancer treatment. |
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---- |
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# Traning Dataset |
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## π€π‘ LiveIdeaBench: Evaluating LLMs' Scientific Creativity and Idea Generation with Minimal Context |
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### Dataset |
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[![Hugging Face Models](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Dataset-yellow)](https://huggingface.co./datasets/6cf/liveideabench) |
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### Paper |
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[![arXiv](https://img.shields.io/badge/arXiv-2412.17596-b31b1b.svg)](https://arxiv.org/abs/2412.17596) |
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If you use this model, please cite: |
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``` |
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@article{ruan2024liveideabench, |
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title={LiveIdeaBench: Evaluating LLMs' Scientific Creativity and Idea Generation with Minimal Context}, |
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author={Kai Ruan and Xuan Wang and Jixiang Hong and Peng Wang and Yang Liu and Hao Sun}, |
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journal={arXiv preprint arXiv:2412.17596}, |
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year={2024} |
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} |
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``` |