karnavivek/Constraint_Learning_LLM

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Model Details

Model Description

This Model is trained on Constraint Learning Concepts (D. Maragno et. al. (2021)). This Concept Helps users to get insights about Integration of Machine learning models into optimization models. This is model is trained on Runpod RTX A5000 with 4-bit Quantization.

Better Version of this model will be released soon.

• Developed by: Vivek Karna
• Funded by [optional]: NA
• Original Concept by [optional]: Donato Maragno
• Model type: Text
• Language(s) (NLP): [More Information Needed]
• License: [More Information Needed]
• Finetuned from model [optional]: [More Information Needed]

Model Sources [optional]

• Repository: https://github.com/karnavivek/askmyprofession.git
• Paper [optional]: Mixed Integer Optimization with Constraint Learning
• Demo [optional]: [More Information Needed]

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

Use the code below 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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Model Card Contact

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