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Lily Cybersecurity 7B V0.2 5.0bpw H6 EXL2 by LoneStriker

 »  All LLMs  »  LoneStriker  »  Lily Cybersecurity 7B V0.2 5.0bpw H6 EXL2   URL Share it on

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  Autotrain compatible Base model:finetune:mistralai/... Base model:mistralai/mistral-7...   Conversational   Cyber security   Cybersecurity   En   Endpoints compatible   Exl2   Finetuned   Hacking   Instruct   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/LoneStriker/Lily-Cybersecurity-7B-v0.2-5.0bpw-h6-exl2 

Lily Cybersecurity 7B V0.2 5.0bpw H6 EXL2 Benchmarks

LLME Score: 0.13442
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Lily Cybersecurity 7B V0.2 5.0bpw H6 EXL2 (LoneStriker/Lily-Cybersecurity-7B-v0.2-5.0bpw-h6-exl2)
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Lily Cybersecurity 7B V0.2 5.0bpw H6 EXL2 Parameters and Internals

Model Type 
cybersecurity assistant, text generation
Use Cases 
Areas:
Research, Commercial applications
Applications:
Cybersecurity training, Information security awareness
Primary Use Cases:
Cybersecurity assistance, Training and educational content
Limitations:
May inherit biases from the base model, Potential for inaccuracies in responses, Legal and ethical use required
Additional Notes 
The model focuses on general knowledge in most areas of cybersecurity.
Supported Languages 
en (fluent)
Training Details 
Data Sources:
22,000 hand-crafted cybersecurity and hacking-related data pairs
Methodology:
Fine-tuned to add context, personality, and styling
Training Time:
24 hours
Hardware Used:
1x A100
Model Architecture:
Mistral Fine-tune
Responsible Ai Considerations 
Transparency:
Consider checking important information. Stay within the law and use ethically.
Input Output 
Input Format:
Instruction-response format
Accepted Modalities:
text
Output Format:
Text responses
LLM NameLily Cybersecurity 7B V0.2 5.0bpw H6 EXL2
Repository 🤗https://huggingface.co/LoneStriker/Lily-Cybersecurity-7B-v0.2-5.0bpw-h6-exl2 
Base Model(s)  mistralai/Mistral-7B-Instruct-v0.2   mistralai/Mistral-7B-Instruct-v0.2
Model Size7b
Required VRAM4.7 GB
Updated2025-09-23
MaintainerLoneStriker
Model Typemistral
Instruction-BasedYes
Model Files  4.7 GB
Supported Languagesen
Quantization Typeexl2
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Lily-Cybersecurity-7B-v0.2-5.0bpw-h6-exl2.

Rank the Lily Cybersecurity 7B V0.2 5.0bpw H6 EXL2 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20241124
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