Swin Transformer (tiny-sized model)
Swin Transformer model trained on ImageNet-1k at resolution 224x224. It was introduced in the paper Swin Transformer: Hierarchical Vision Transformer using Shifted Windows by Liu et al. and first released in this repository.
Model Description
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Model Sources [optional]
- **Repository:**kaikhosrotav
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Uses
Direct 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
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Training Hyperparameters
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Evaluation
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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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