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README.md
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## Direct Use
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The model is directly integrated into Credential Digger and can be used to filter the false positive discoveries of a scan
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## Downstream Use [Optional]
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More information needed.
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## Out-of-Scope Use
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The model should not be used to intentionally create hostile or alienating environments for people.
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# Bias, Risks, and Limitations
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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.
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## Recommendations
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recomendations.
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# Training Details
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**BibTeX:**
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```
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author = {S. Lounici and M. Rosa and C. M. Negri and S. Trabelsi and M. Önen},
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booktitle = {Proc. of the 8th The International Conference on Information Systems Security and Privacy (ICISSP)},
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title = {Optimizing Leak Detection in Open-Source Platforms with Machine Learning Techniques},
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month = {February},
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day = {11-13},
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year = {2021}
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}
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# Glossary [optional]
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More information needed
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# More Information [optional]
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More information needed
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# Model Card Authors [optional]
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SAP OSS in collaboration with Ezi Ozoani and the Hugging Face team.
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## Direct Use
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The model is directly integrated into [Credential Digger]((https://github.com/SAP/credential-digger) and can be used to filter the false positive password discoveries of a scan.
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## Out-of-Scope Use
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The model should not be used to intentionally create hostile or alienating environments for people.
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# Training Details
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**BibTeX:**
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```
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TBD
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```
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# Model Card Authors [optional]
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SAP OSS in collaboration with Ezi Ozoani and the Hugging Face team.
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