CiPE-clinically-intelligient-prediction-engine-neural-7b

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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• Training data: [Briefly describe the dataset used for training. Include any data cleaning or preprocessing steps.]

Intended Use

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• Use cases: [Describe potential use cases for the model.]

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

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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

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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

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Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

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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

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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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APA:

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Glossary [optional]

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