Model Card for Model ID
The CiPE GenAI project is a revolutionary tool designed to improve medication management and safety by providing alerts for potential drug interactions and side effects using Generative AI technology.
Model Details
Model Description
- Developed by: Shubhankar Tripathy, Sid Vijay, Jiyeon Song, Aditi Killedar
- Funded by [optional]: [More Information Needed]
- Shared by [optional]:
- Model type: Fine-Tuned RAG Model
- Language(s) (NLP): [More Information Needed]
- License: [More Information Needed]
- Finetuned from model [optional]: Neural-Chat-7B
Model Card for My Fine-Tuned Model
Model Description
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- Model architecture: [Specify the architecture, e.g., BERT, GPT-2, etc.]
- Training data: [Briefly describe the dataset used for training. Include any data cleaning or preprocessing steps.]
Intended Use
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Limitations
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Hardware
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Software Optimizations
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Ethical Considerations
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More Information
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- Repository: https://github.com/lonexreb/CiPE
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Uses
Direct Use
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Downstream Use [optional]
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
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Training Details
Training Data
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
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Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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Summary
Model Examination [optional]
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Hardware
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Software
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Citation [optional]
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