🚀 Model Card for Model ID
This is a model card for a transformers model pushed on the Hub. It provides comprehensive information about the model, including its details, uses, training, evaluation, and more.
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Model Details
Model Description
This is the model card of a 🤖 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Uses
Direct Use
This section is for the model use without fine-tuning or plugging into a larger ecosystem/app.
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Downstream Use [optional]
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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Out-of-Scope Use
This section addresses misuse, malicious use, and uses that the model will not work well for.
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Bias, Risks, and Limitations
This section is meant to convey both technical and sociotechnical limitations.
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Recommendations
💡 Usage Tip
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]
This section provides information about throughput, start/end time, checkpoint size if relevant, etc.
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
These are the things the evaluation is disaggregating by, e.g., subpopulations or domains.
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Metrics
These are the evaluation metrics being used, ideally with a description of why.
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Results
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Summary
Model Examination [optional]
Relevant interpretability work for the model goes here.
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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
Hardware
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Software
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Glossary [optional]
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Model Card Authors [optional]
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