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This is a model card for a đ¤ transformers model pushed on the Hub. It provides an overview of the model's details, uses, training, evaluation, and other relevant information.
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⨠Features
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Model Details
This is the model card of a đ¤ transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Developed by | [More Information Needed] |
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Model Type | [More Information Needed] |
Language(s) (NLP) | [More Information Needed] |
License | [More Information Needed] |
Finetuned from model [optional] | [More Information Needed] |
Model Sources [optional]
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Uses
Direct Use
This section is for the model use without fine - tuning or plugging into a larger ecosystem/app. However, more information is needed.
Downstream Use [optional]
This section is for the model use when fine - tuned for a task, or when plugged into a larger ecosystem/app. More information is required.
Out - of - Scope Use
This section addresses misuse, malicious use, and uses that the model will not work well for. Currently, more information is needed.
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 is needed for further recommendations.
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
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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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Carbon Emitted | [More Information Needed] |
Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
Hardware
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Software
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Citation [optional]
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Glossary [optional]
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Model Card Contact
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