
# Model Card for model-card-testing

<!-- Provide a quick summary of what the model is/does. [Optional] -->
This is a placeholder summary.


<details>
<summary> Click to expand policymaker version of model card </summary>

# Table of Contents 

1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Model Examination](#model-examination)
5. [Environmental Impact](#environmental-impact)
6. [Citation](#citation)
7. [Glossary](#glossary-optional)
8. [More Information](#more-information-optional)
9. [Model Card Authors](#model-card-authors-optional)
10. [Model Card Contact](#model-card-contact)

</details>

#  Table of Contents

1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training Details](#training-details)
5. [Evaluation](#evaluation)
6. [Model Examination](#model-examination)
7. [Environmental Impact](#environmental-impact)
8. [Technical Specifications](#technical-specifications-optional)
9. [Citation](#citation)
10. [Glossary](#glossary-optional)
11. [More Information](#more-information-optional)
12. [Model Card Authors](#model-card-authors-optional)
13. [Model Card Contact](#model-card-contact)
14. [How To Get Started With the Model](#how-to-get-started-with-the-model)


# Model Details

## Model Description

<!-- Provide a longer summary of what this model is/does. -->


- **Developed by:** More information needed
- **Shared by [Optional]:** More information needed
- **Model type:** Language model
- **Language(s) (NLP):** More information needed
- **License:** More information needed
- **Related Models:** fake_model1, fake_model2
    - **Parent Model:** More information needed
- **Resources for more information:** More information needed

    - [Associated Paper](https://huggingface.co) 
    - [Blog Post](https://huggingface.co)

# 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. -->
<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->

The model can be used for text generation.


## Downstream Use [Optional]

<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->
 
To learn more about this task and potential downstream uses, see the Hugging Face [text generation docs](https://huggingface.co/tasks/text-generation)


## Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
<!-- If the user enters content, print that. If not, but they enter a task in the list, use that. If neither, say "more info needed." -->

The model should not be used to intentionally create hostile or alienating environments for people. The model was not trained to be factual or true representations of people or events, and therefore using the models to generate such content is out-of-scope for the abilities of this model.


# Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.


## Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->


Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recomendations.


# Training Details

## Training Data

<!-- This should link to a Data 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. -->

More information on training data needed


## 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

More information needed

### Speeds, Sizes, Times

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

More information needed
 
# Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

## Testing Data, Factors & Metrics

### Testing Data

<!-- This should link to a Data Card if possible. -->

More information needed


### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

More information needed

### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

More information needed

## Results 

More information needed

# Model Examination

More information needed

# 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](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** More information needed
- **Hours used:** More information needed
- **Cloud Provider:** More information needed
- **Compute Region:** More information needed
- **Carbon Emitted:** More information needed

# Technical Specifications [optional]

## Model Architecture and Objective

More information needed

## Compute Infrastructure

More information needed

### Hardware

More information needed

### Software

More information needed

# Citation

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

More information needed

**APA:**

More information needed

# Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->

More information needed

# More Information [optional]

More information needed

# Model Card Authors [optional]

<!-- This section provides another layer of transparency and accountability. Whose views is this model card representing? How many voices were included in its construction? Etc. -->

More information needed

# Model Card Contact

More information needed

# How to Get Started with the Model

Use the code below to get started with the model.

<details>
<summary> Click to expand </summary>

More information needed

</details>
{"language": ["en", "fr", "multilingual"], "license": "mit"}
en fr multilingual arxiv:1910.09700 license:mit region:us
TAGS
#en #fr #multilingual #arxiv-1910.09700 #license-mit #region-us 


# Model Card for model-card-testing


This is a placeholder summary.


<details>
<summary> Click to expand policymaker version of model card </summary>

# Table of Contents 

1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Model Examination
5. Environmental Impact
6. Citation
7. Glossary
8. More Information
9. Model Card Authors
10. Model Card Contact

</details>

#  Table of Contents

1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Training Details
5. Evaluation
6. Model Examination
7. Environmental Impact
8. Technical Specifications
9. Citation
10. Glossary
11. More Information
12. Model Card Authors
13. Model Card Contact
14. How To Get Started With the Model


# Model Details

## Model Description




- Developed by: More information needed
- Shared by [Optional]: More information needed
- Model type: Language model
- Language(s) (NLP): More information needed
- License: More information needed
- Related Models: fake_model1, fake_model2
    - Parent Model: More information needed
- Resources for more information: More information needed

    - Associated Paper 
    - Blog Post

# Uses



## Direct Use




The model can be used for text generation.


## Downstream Use [Optional]



 
To learn more about this task and potential downstream uses, see the Hugging Face text generation docs


## Out-of-Scope Use




The model should not be used to intentionally create hostile or alienating environments for people. The model was not trained to be factual or true representations of people or events, and therefore using the models to generate such content is out-of-scope for the abilities of this model.


# Bias, Risks, and Limitations



Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.


## Recommendations




Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recomendations.


# Training Details

## Training Data



More information on training data needed


## Training Procedure



### Preprocessing

More information needed

### Speeds, Sizes, Times



More information needed
 
# Evaluation



## Testing Data, Factors & Metrics

### Testing Data



More information needed


### Factors



More information needed

### Metrics



More information needed

## Results 

More information needed

# Model Examination

More information needed

# Environmental Impact



Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

- Hardware Type: More information needed
- Hours used: More information needed
- Cloud Provider: More information needed
- Compute Region: More information needed
- Carbon Emitted: More information needed

# Technical Specifications [optional]

## Model Architecture and Objective

More information needed

## Compute Infrastructure

More information needed

### Hardware

More information needed

### Software

More information needed

BibTeX:

More information needed

APA:

More information needed

# Glossary [optional]



More information needed

# More Information [optional]

More information needed

# Model Card Authors [optional]



More information needed

# Model Card Contact

More information needed

# How to Get Started with the Model

Use the code below to get started with the model.

<details>
<summary> Click to expand </summary>

More information needed

</details>
# Model Card for model-card-testing


This is a placeholder summary.


<details>
<summary> Click to expand policymaker version of model card </summary> # Table of Contents 

1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Model Examination
5. Environmental Impact
6. Citation
7. Glossary
8. More Information
9. Model Card Authors
10. Model Card Contact

</details> #  Table of Contents

1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Training Details
5. Evaluation
6. Model Examination
7. Environmental Impact
8. Technical Specifications
9. Citation
10. Glossary
11. More Information
12. Model Card Authors
13. Model Card Contact
14. How To Get Started With the Model # Model Details ## Model Description




- Developed by: More information needed
- Shared by [Optional]: More information needed
- Model type: Language model
- Language(s) (NLP): More information needed
- License: More information needed
- Related Models: fake_model1, fake_model2
    - Parent Model: More information needed
- Resources for more information: More information needed

    - Associated Paper 
    - Blog Post # Uses ## Direct Use




The model can be used for text generation. ## Downstream Use [Optional]



 
To learn more about this task and potential downstream uses, see the Hugging Face text generation docs ## Out-of-Scope Use




The model should not be used to intentionally create hostile or alienating environments for people. The model was not trained to be factual or true representations of people or events, and therefore using the models to generate such content is out-of-scope for the abilities of this model. # Bias, Risks, and Limitations



Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. ## Recommendations




Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recomendations. # Training Details ## Training Data



More information on training data needed ## Training Procedure ### Preprocessing

More information needed ### Speeds, Sizes, Times



More information needed # Evaluation ## Testing Data, Factors & Metrics ### Testing Data



More information needed ### Factors



More information needed ### Metrics



More information needed ## Results 

More information needed # Model Examination

More information needed # Environmental Impact



Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

- Hardware Type: More information needed
- Hours used: More information needed
- Cloud Provider: More information needed
- Compute Region: More information needed
- Carbon Emitted: More information needed # Technical Specifications [optional] ## Model Architecture and Objective

More information needed ## Compute Infrastructure

More information needed ### Hardware

More information needed ### Software

More information needed

BibTeX:

More information needed

APA:

More information needed # Glossary [optional]



More information needed # More Information [optional]

More information needed # Model Card Authors [optional]



More information needed # Model Card Contact

More information needed # How to Get Started with the Model

Use the code below to get started with the model.

<details>
<summary> Click to expand </summary>

More information needed

</details>
TAGS
#en #fr #multilingual #arxiv-1910.09700 #license-mit #region-us 
 # Model Card for model-card-testing


This is a placeholder summary.


<details>
<summary> Click to expand policymaker version of model card </summary> # Table of Contents 

1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Model Examination
5. Environmental Impact
6. Citation
7. Glossary
8. More Information
9. Model Card Authors
10. Model Card Contact

</details> #  Table of Contents

1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Training Details
5. Evaluation
6. Model Examination
7. Environmental Impact
8. Technical Specifications
9. Citation
10. Glossary
11. More Information
12. Model Card Authors
13. Model Card Contact
14. How To Get Started With the Model # Model Details ## Model Description




- Developed by: More information needed
- Shared by [Optional]: More information needed
- Model type: Language model
- Language(s) (NLP): More information needed
- License: More information needed
- Related Models: fake_model1, fake_model2
    - Parent Model: More information needed
- Resources for more information: More information needed

    - Associated Paper 
    - Blog Post # Uses ## Direct Use




The model can be used for text generation. ## Downstream Use [Optional]



 
To learn more about this task and potential downstream uses, see the Hugging Face text generation docs ## Out-of-Scope Use




The model should not be used to intentionally create hostile or alienating environments for people. The model was not trained to be factual or true representations of people or events, and therefore using the models to generate such content is out-of-scope for the abilities of this model. # Bias, Risks, and Limitations



Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. ## Recommendations




Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recomendations. # Training Details ## Training Data



More information on training data needed ## Training Procedure ### Preprocessing

More information needed ### Speeds, Sizes, Times



More information needed # Evaluation ## Testing Data, Factors & Metrics ### Testing Data



More information needed ### Factors



More information needed ### Metrics



More information needed ## Results 

More information needed # Model Examination

More information needed # Environmental Impact



Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

- Hardware Type: More information needed
- Hours used: More information needed
- Cloud Provider: More information needed
- Compute Region: More information needed
- Carbon Emitted: More information needed # Technical Specifications [optional] ## Model Architecture and Objective

More information needed ## Compute Infrastructure

More information needed ### Hardware

More information needed ### Software

More information needed

BibTeX:

More information needed

APA:

More information needed # Glossary [optional]



More information needed # More Information [optional]

More information needed # Model Card Authors [optional]



More information needed # Model Card Contact

More information needed # How to Get Started with the Model

Use the code below to get started with the model.

<details>
<summary> Click to expand </summary>

More information needed

</details>
passage: TAGS
#en #fr #multilingual #arxiv-1910.09700 #license-mit #region-us 
# Model Card for model-card-testing


This is a placeholder summary.


<details>
<summary> Click to expand policymaker version of model card </summary># Table of Contents 

1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Model Examination
5. Environmental Impact
6. Citation
7. Glossary
8. More Information
9. Model Card Authors
10. Model Card Contact

</details>#  Table of Contents

1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Training Details
5. Evaluation
6. Model Examination
7. Environmental Impact
8. Technical Specifications
9. Citation
10. Glossary
11. More Information
12. Model Card Authors
13. Model Card Contact
14. How To Get Started With the Model# Model Details## Model Description




- Developed by: More information needed
- Shared by [Optional]: More information needed
- Model type: Language model
- Language(s) (NLP): More information needed
- License: More information needed
- Related Models: fake_model1, fake_model2
    - Parent Model: More information needed
- Resources for more information: More information needed

    - Associated Paper 
    - Blog Post# Uses## Direct Use




The model can be used for text generation.## Downstream Use [Optional]



 
To learn more about this task and potential downstream uses, see the Hugging Face text generation docs## Out-of-Scope Use




The model should not be used to intentionally create hostile or alienating environments for people. The model was not trained to be factual or true representations of people or events, and therefore using the models to generate such content is out-of-scope for the abilities of this model.# Bias, Risks, and Limitations



Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.