Model Card for Model ID

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Model Details

Model Description

This model identifies diseases in a tomato plant.<!-- Provide a longer summary of what this model is. -->

• **Developed by: Sudhir
• Shared by [optional]: [More Information Needed]
• **Model type: Computer Vision
• **Language(s) (NLP): Python
• **License: Other
• Finetuned from model [optional]: [More Information Needed]

Model Sources [optional]

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• **Repository: https://github.com/sudhir2016/Google-Colab-11
• Paper [optional]: [More Information Needed]
• Demo [optional]: [More Information Needed]

Uses

Tomato plant disease detection.

Direct Use

Direct use

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Downstream Use [optional]

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Out-of-Scope Use

NA

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Bias, Risks, and Limitations

NA

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Recommendations

NA

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

Will link to a demo

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Training Details

Training Data

NA [More Information Needed]

Training Procedure

NA

Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

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).

• Hardware Type: [More Information Needed]
• Hours used: [More Information Needed]
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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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BibTeX:

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APA:

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Glossary [optional]

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Model Card Authors [optional]

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Model Card Contact

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