Cyber Risk Llama 3 8B by Vanessasml

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Cyber Risk Llama 3 8B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Cyber Risk Llama 3 8B (Vanessasml/cyber-risk-llama-3-8b)

Cyber Risk Llama 3 8B Parameters and Internals

Model Type 
text generation
Use Cases 
Applications:
Cybersecurity applications
Primary Use Cases:
Generating and understanding cybersecurity data, Identifying cyber threats, Classifying data under the NIST taxonomy and IT Risks
Limitations:
Not to be used for medical advice, legal decisions, or life-critical systems
Additional Notes 
The model was evaluated based on the qualitative assessment of generated text relevance and coherence in cybersecurity contexts.
Training Details 
Data Sources:
vanessasml/cybersecurity_32k_instruction_input_output
Methodology:
Fine-tuning
Hardware Used:
GPUs with mixed precision (FP16/BF16) enabled
LLM NameCyber Risk Llama 3 8B
Repository ๐Ÿค—https://huggingface.co/Vanessasml/cyber-risk-llama-3-8b 
Model Size8b
Required VRAM16.1 GB
Updated2025-02-22
MaintainerVanessasml
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-2   6.1 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.31.0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Vanessasml/cyber-risk-llama-3-8b.

Rank the Cyber Risk Llama 3 8B Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227