library_name: peft base_model: models/meta-llama_Meta-Llama-3-8B
Model Card for Model ID
Cyber Threat Intelligence (CTI) fine-tune LoRA Adapter.
Trained on the ORKL-cleaned-small dataset.
Model Details
Model Description
- Developed by: Aaron Kaplan, Juergen Brandl (AI Security SIG at FIRST)
- Funded by [optional]: unfortunately no one
- Model type: LLama-3-8B-instruct
- License: AGPL-3.0
- Finetuned from model [optional]: meta-llama-llama-3-8b
Model Sources [optional]
- Repository: [More Information Needed]
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Uses
Use this at your own risk, but apart from that... it's a LoRA that you can stack on top of either other LoRAs and/or on top of meta-llama/llama-3-8b-instruct.
losses etc.
Downstream Use [optional]
CTI texts.
Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
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Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Factors
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Metrics
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Results
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Summary
Model Examination [optional]
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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]
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Technical Specifications [optional]
Model Architecture and Objective
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Compute Infrastructure
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Hardware
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Software
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Citation [optional]
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APA:
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Glossary [optional]
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Model Card Authors [optional]
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Model Card Contact
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Framework versions
- PEFT 0.8.2