For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
Doc / guide: https://huggingface.co/docs/hub/model-cards
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Model Card for TSOTSALLM
<!-- Provide a quick summary of what the model is/does. -->
Model Details
Model Description
<!-- Provide a longer summary of what this model is. -->
Model Sources [optional]
<!-- Provide the basic links for the model. -->
Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
Direct Use
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
How to Get Started with the Model
Training Details
Training Data
<!-- This should link to a Dataset 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. -->
Training Procedure
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
Preprocessing [optional]
Training Hyperparameters
Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
Testing Data, Factors & Metrics
Testing Data
<!-- This should link to a Dataset Card if possible. -->
Factors
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
Metrics
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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Results
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Summary
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Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
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Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
Technical Specifications [optional]
Model Architecture and Objective
Compute Infrastructure
Hardware
Software
Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
