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  # Model Card for Model ID
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  <!-- Provide a quick summary of what the model is/does. -->
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- This is a Llama 3 model finetuned on execution logs to be used for system anomaly detections.
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  ## Model Details
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  This model was finetuned on a variety of system logs of a sock shop app. Given a log chunk of 10 messages, it generates the next log message according to normal execution.
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- - **Developed by:** [Luís Almeida, Diego Pedroso, Lucas Pulcinelli, William Aisawa, Sarita Bruschi, Inês Dutra]
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  - **Funded by [optional]:** [More Information Needed]
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  - **Shared by [optional]:** [More Information Needed]
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  - **Model type:** [More Information Needed]
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  <!-- Provide the basic links for the model. -->
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- - **Repository:** [https://github.com/lasdpc-icmc/maia]
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  - **Paper [optional]:** [More Information Needed]
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  - **Demo [optional]:** [More Information Needed]
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  ## Uses
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  <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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-
 
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  ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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  [More Information Needed]
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  ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-
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- [More Information Needed]
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-
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- ## Bias, Risks, and Limitations
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-
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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-
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- [More Information Needed]
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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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 recommendations.
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  ## How to Get Started with the Model
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- Use the code below to get started with the model.
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-
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- [More Information Needed]
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  ## Training Details
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  # Model Card for Model ID
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  <!-- Provide a quick summary of what the model is/does. -->
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+ This is a Llama 3 model finetuned on execution logs to be used for a sock-shop app anomaly detections.
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  ## Model Details
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  This model was finetuned on a variety of system logs of a sock shop app. Given a log chunk of 10 messages, it generates the next log message according to normal execution.
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+ - **Developed by:** Luís Almeida, Diego Pedroso, Lucas Pulcinelli, William Aisawa, Sarita Bruschi, Inês Dutra
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  - **Funded by [optional]:** [More Information Needed]
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  - **Shared by [optional]:** [More Information Needed]
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  - **Model type:** [More Information Needed]
 
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  <!-- Provide the basic links for the model. -->
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+ - **Repository:** https://github.com/lasdpc-icmc/maia
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  - **Paper [optional]:** [More Information Needed]
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  - **Demo [optional]:** [More Information Needed]
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  ## Uses
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  <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+ Since the model was finetuned on execution logs of the sock-shop app, it is intended to be used to generate logs of said app. To adapt it to another system, it should be
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+ finetuned on a sample of execution logs of the new system.
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  ### Direct Use
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+ Direct plugin to the sock-shop app.
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  [More Information Needed]
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  ### Out-of-Scope Use
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+ The usage of this model on execution logs that it hasn't been finetuned on may yield bad results.
 
 
 
 
 
 
 
 
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+ We recommend users to finetune this model on logs of their app before they use it.
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  ## How to Get Started with the Model
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+ Please refer to https://github.com/lasdpc-icmc/maia/apps/llm for the code files that were developed for this model. The file "eval_llm.py" provides code to detect system
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+ anomalies.
 
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  ## Training Details
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