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CyberSecQwen 4B by lablab-ai-amd-developer-hackathon

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CyberSecQwen 4B is an open-source language model by lablab-ai-amd-developer-hackathon. Features: 4b LLM, VRAM: 8GB, Context: 256K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.29.

  Arxiv:2504.21039   Arxiv:2510.14113   Amd Base model:adapter:qwen/qwen3-... Base model:qwen/qwen3-4b-instr...   Conversational   Cti   Cwe-classification   Cybersecurity   En   Endpoints compatible   Flash-attention-2   Instruct   Lora   Mi300x   Model-index   Peft   Qwen3   Region:us   Rocm   Safetensors   Security   Vulnerability-analysis
Model Card on HF 🤗: https://huggingface.co/lablab-ai-amd-developer-hackathon/CyberSecQwen-4B 

CyberSecQwen 4B Benchmarks

LLME Score: 0.2873
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CyberSecQwen 4B (lablab-ai-amd-developer-hackathon/CyberSecQwen-4B)
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CyberSecQwen 4B Parameters and Internals

LLM NameCyberSecQwen 4B
Repository 🤗https://huggingface.co/lablab-ai-amd-developer-hackathon/CyberSecQwen-4B 
Base Model(s)  Qwen3 4B Instruct 2507   Qwen/Qwen3-4B-Instruct-2507
Model Size4b
Required VRAM8 GB
Updated2026-06-27
Maintainerlablab-ai-amd-developer-hackathon
Model Typeqwen3
Instruction-BasedYes
Model Files  8.0 GB
Supported Languagesen
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length262144
Model Max Length262144
Transformers Version5.7.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Errorsreplace

Best Alternatives to CyberSecQwen 4B

Best Alternatives
Context / RAM
Downloads
Likes
FastContext 1.0 4B SFT256K / 8.1 GB5735357
FastContext 1.0 4B RL256K / 8.1 GB455961
Qwen3 4B Instruct 2507256K / 8.1 GB5455321886
Qwen3 4B Instruct 2507 FP8256K / 5.2 GB84028179
Agents K1256K / 8.8 GB60120
Qwen3 4B Elderly Sft Merged256K / 8.1 GB3780
Jan Code 4B256K / 8.9 GB41778
Qwen3 4B DASD 32K256K / 8 GB850
Qwen3 4B Instruct 2507256K / 8.1 GB4128426
Jan V3.5 4B256K / 8.9 GB45716
Note: green Score (e.g. "73.2") means that the model is better than lablab-ai-amd-developer-hackathon/CyberSecQwen-4B.

Rank the CyberSecQwen 4B 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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