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--- |
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license: cc-by-nc-4.0 |
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datasets: |
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- NingLab/MuMOInstruct |
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language: |
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- en |
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base_model: |
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- mistralai/Mistral-7B-Instruct-v0.3 |
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pipeline_tag: text-generation |
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tags: |
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- chemistry |
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- molecule optimization |
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--- |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** https://github.com/ninglab/GeLLMO |
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- **Paper:** Coming soon |
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## Usage |
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For instructions to run the model, please refer to our repository. |
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## Bias, Risks, and Limitations |
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While our models are designed for research and drug discovery applications, |
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they come with ethical and safety considerations: |
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1. **Potential for Misuse:** Although the model is not explicitly designed to generate toxic, |
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controlled, or harmful compounds, adversarial prompts or unintended biases in the pretrained model |
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may lead to the generation of undesirable molecules. |
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2. **Unintended Harmful Outputs:** The model does not inherently filter out molecules with high toxicity, |
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abuse potential, or environmental hazards. Users must implement additional safeguards to prevent misuse. |
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3. **Absence of Built-in Safety Mechanisms:** The model does not incorporate explicit regulatory or |
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safety filters (e.g., toxicity or compliance checks). |
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It is the responsibility of users to validate generated molecules for safety and ethical considerations. |
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We urge users to adopt best practices, including toxicity prediction pipelines, |
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ethical oversight, and responsible AI usage policies, to prevent harmful applications of this model. |
