readme: ---
  language:
  - en
  license: mit
  library_name: pytorch
  tags:
  - modelcards
  - autogenerated-modelcard
  datasets:
  - beans
  metrics:
  - accuracy
  ---
  
  # modelcard-creator-demo
  
  ## Table of Contents
  - [Model Details](#model-details)
  - [How To Get Started With the Model](#how-to-get-started-with-the-model)
  - [Uses](#uses)
    - [Direct Use](#direct-use)
    - [Downstream Use](#downstream-use)
    - [Misuse and Out of Scope Use](#misuse-and-out-of-scope-use)
  - [Limitations and Biases](#limitations-and-biases)
  - [Training](#training)
    - [Training Data](#training-data)
    - [Training Procedure](#training-procedure)
  - [Evaluation Results](#evaluation-results)
  - [Environmental Impact](#environmental-impact)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  
  
  ## Model Details
  
  <!-- Give an overview of your model, the relevant research paper, who trained it, etc.  -->
  
  This isn't really a model, it's just a test repo to see if the [model card creator](https://huggingface.co/spaces/nateraw/modelcard-creator) works!
  
  
  - Developed by: Nathan Raw
  - Language(s): 
  - License: modelcard-creator-demo is licensed under the mit license
  - Resources for more information:
    - [Research Paper](https://arxiv.org/pdf/1810.03993.pdf)
    - [GitHub Repo](https://github.com/nateraw/modelcards)
  
  
  ## How to Get Started with the Model 
  
  Use the code below to get started with the model.
  
  ```python
  # A nice code snippet here that describes how to use the model...
  ```
  
  ## Uses
  
  #### Direct Use
  
  <!-- Describe what kind of tasks this model can be used for directly or problems it can solve. -->
  
  [More Information Needed]
  
  #### Downstream Use
  
  <!-- Describe how this model could be leveraged by a downstream model (if applicable) -->
  
  [More Information Needed]
  
  #### Misuse and Out-of-scope Use
  
  <!-- Describe ways in which this model ***should not*** be used. -->
  
  [More Information Needed]
  
  ## Limitations and Biases
  
  <!-- Describe limitations and biases of this model or models of it's type. -->
  
  **CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propogate historical and current stereotypes.**
  
  [More Information Needed]
  
  ## Training
  
  #### Training Data
  
  <!-- Describe the dataset used to train this model. -->
  <!-- Refer to data card if dataset is provided and exists on the hub -->
  
  See the data card for additional information.
  
  #### Training Procedure
  
  <!-- Describe the preprocessing, hardware used, training hyperparameters, etc. -->
  
  [More Information Needed]
  
  ## Evaluation Results
  
  <!-- Describe evaluation results of this model across any datasets it was evaluated on. -->
  
  [More Information Needed]
  
  ## Environmental Impact
  
  <!-- Provide information to document the environmental impact of this model -->
  
  You can estimate carbon emissions using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700)
  
  - **Hardware Type:** 
  - **Hours used:** 
  - **Cloud Provider:** 
  - **Compute Region:** 
  - **Carbon Emitted:** 
  
  
  ## Citation Information
  
  ```bibtex
  @inproceedings{Mitchell_2019,
  	doi = {10.1145/3287560.3287596},
    
  	url = {https://doi.org/10.1145%2F3287560.3287596},
    
  	year = 2019,
  	month = {jan},
    
  	publisher = {{ACM}
  },
    
  	author = {Margaret Mitchell and Simone Wu and Andrew Zaldivar and Parker Barnes and Lucy Vasserman and Ben Hutchinson and Elena Spitzer and Inioluwa Deborah Raji and Timnit Gebru},
    
  	title = {Model Cards for Model Reporting},
    
  	booktitle = {Proceedings of the Conference on Fairness, Accountability, and Transparency}
  }
  ```