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ConvNext_Multi_model_card.md
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| 1 |
+
---
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| 2 |
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| 3 |
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---
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| 7 |
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| 9 |
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| 10 |
+
# Model Card for ConvNext_Multi
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| 11 |
+
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| 12 |
+
<!-- Provide a quick summary of what the model is/does. [Optional] -->
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| 13 |
+
다중분광 영상 데이터를 입력으로 받아 작물의 생육 조건 분류 작업을 수행하는 최신 ConvNeXt 기반 딥러닝 모델입니다. 효율적인 멀티밴드 특성 학습을 통해 다중분광 이미지 분석에 최적화되어 있습니다.
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| 14 |
+
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| 15 |
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| 16 |
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| 17 |
+
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| 18 |
+
# Table of Contents
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| 19 |
+
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+
- [Model Card for ConvNext_Multi](#model-card-for--model_id-)
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| 21 |
+
- [Table of Contents](#table-of-contents)
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| 22 |
+
- [Table of Contents](#table-of-contents-1)
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| 23 |
+
- [Model Details](#model-details)
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| 24 |
+
- [Model Description](#model-description)
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| 25 |
+
- [Uses](#uses)
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| 26 |
+
- [Direct Use](#direct-use)
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| 27 |
+
- [Downstream Use [Optional]](#downstream-use-optional)
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| 28 |
+
- [Out-of-Scope Use](#out-of-scope-use)
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| 29 |
+
- [Bias, Risks, and Limitations](#bias-risks-and-limitations)
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| 30 |
+
- [Recommendations](#recommendations)
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| 31 |
+
- [Training Details](#training-details)
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| 32 |
+
- [Training Data](#training-data)
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| 33 |
+
- [Training Procedure](#training-procedure)
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| 34 |
+
- [Preprocessing](#preprocessing)
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| 35 |
+
- [Speeds, Sizes, Times](#speeds-sizes-times)
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| 36 |
+
- [Evaluation](#evaluation)
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| 37 |
+
- [Testing Data, Factors & Metrics](#testing-data-factors--metrics)
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| 38 |
+
- [Testing Data](#testing-data)
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| 39 |
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- [Factors](#factors)
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| 40 |
+
- [Metrics](#metrics)
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| 41 |
+
- [Results](#results)
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| 42 |
+
- [Model Examination](#model-examination)
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| 43 |
+
- [Environmental Impact](#environmental-impact)
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| 44 |
+
- [Technical Specifications [optional]](#technical-specifications-optional)
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| 45 |
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- [Model Architecture and Objective](#model-architecture-and-objective)
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| 46 |
+
- [Compute Infrastructure](#compute-infrastructure)
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| 47 |
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- [Hardware](#hardware)
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| 48 |
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- [Software](#software)
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| 49 |
+
- [Citation](#citation)
|
| 50 |
+
- [Glossary [optional]](#glossary-optional)
|
| 51 |
+
- [More Information [optional]](#more-information-optional)
|
| 52 |
+
- [Model Card Authors [optional]](#model-card-authors-optional)
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| 53 |
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- [Model Card Contact](#model-card-contact)
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| 54 |
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- [How to Get Started with the Model](#how-to-get-started-with-the-model)
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| 55 |
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| 56 |
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| 57 |
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# Model Details
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| 58 |
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| 59 |
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## Model Description
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| 60 |
+
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| 61 |
+
<!-- Provide a longer summary of what this model is/does. -->
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| 62 |
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다중분광 영상 데이터를 입력으로 받아 작물의 생육 조건 분류 작업을 수행하는 최신 ConvNeXt 기반 딥러닝 모델입니다. 효율적인 멀티밴드 특성 학습을 통해 다중분광 이미지 분석에 최적화되어 있습니다.
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| 63 |
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| 64 |
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- **Developed by:** More information needed
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| 65 |
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- **Shared by [Optional]:** More information needed
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| 66 |
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- **Model type:** Language model
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| 67 |
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- **Language(s) (NLP):** ko
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| 68 |
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- **License:** mit
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| 69 |
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- **Parent Model:** More information needed
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| 70 |
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- **Resources for more information:** More information needed
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- [Associated Paper](Liu et al., "ConvNeXt: A ConvNet for the 2020s," arXiv:2201.03545)
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| 73 |
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# Uses
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| 75 |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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| 77 |
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| 78 |
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## Direct Use
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| 79 |
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| 80 |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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| 81 |
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<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
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| 82 |
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| 83 |
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| 84 |
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| 85 |
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| 86 |
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## Downstream Use [Optional]
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| 87 |
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| 88 |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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| 89 |
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<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
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| 90 |
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| 93 |
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| 94 |
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## Out-of-Scope Use
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| 95 |
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| 96 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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| 97 |
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<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
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| 98 |
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| 99 |
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| 101 |
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# Bias, Risks, and Limitations
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| 103 |
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| 104 |
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
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## Recommendations
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| 110 |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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| 112 |
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# Training Details
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| 118 |
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| 119 |
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## Training Data
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| 120 |
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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| 122 |
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More information on training data needed
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| 124 |
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## Training Procedure
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| 127 |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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| 129 |
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### Preprocessing
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| 131 |
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More information needed
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| 133 |
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| 134 |
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### Speeds, Sizes, Times
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| 135 |
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| 136 |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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| 137 |
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| 138 |
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More information needed
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| 139 |
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| 140 |
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# Evaluation
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| 141 |
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<!-- This section describes the evaluation protocols and provides the results. -->
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| 143 |
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## Testing Data, Factors & Metrics
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| 145 |
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| 146 |
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### Testing Data
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| 147 |
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| 148 |
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<!-- This should link to a Data Card if possible. -->
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| 149 |
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| 150 |
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More information needed
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| 151 |
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| 152 |
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| 153 |
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### Factors
|
| 154 |
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| 155 |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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| 156 |
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More information needed
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| 158 |
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| 159 |
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### Metrics
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| 160 |
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| 161 |
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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| 162 |
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| 163 |
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More information needed
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| 164 |
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| 165 |
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## Results
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| 166 |
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| 167 |
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More information needed
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| 168 |
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| 169 |
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# Model Examination
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| 170 |
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| 171 |
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More information needed
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| 172 |
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| 173 |
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# Environmental Impact
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| 174 |
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| 175 |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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| 176 |
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| 177 |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** More information needed
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| 180 |
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- **Hours used:** More information needed
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| 181 |
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- **Cloud Provider:** More information needed
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| 182 |
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- **Compute Region:** More information needed
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| 183 |
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- **Carbon Emitted:** More information needed
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| 184 |
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| 185 |
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# Technical Specifications [optional]
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## Model Architecture and Objective
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| 188 |
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| 189 |
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More information needed
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| 190 |
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| 191 |
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## Compute Infrastructure
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| 192 |
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More information needed
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| 194 |
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### Hardware
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| 196 |
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More information needed
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| 198 |
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### Software
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| 200 |
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More information needed
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# Citation
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| 204 |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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More information needed
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**APA:**
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More information needed
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# Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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More information needed
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# More Information [optional]
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More information needed
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# Model Card Authors [optional]
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<!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. -->
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MuhanRnd
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# Model Card Contact
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More information needed
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# How to Get Started with the Model
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Use the code below to get started with the model.
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<details>
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<summary> Click to expand </summary>
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More information needed
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</details>
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