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CodeAstra 7B by rootxhacker

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CodeAstra 7B is an open-source language model by rootxhacker. Features: 7b LLM, License: apache-2.0, LLM Explorer Score: 0.15.

  4-bit   Adapter   Bitsandbytes   Code   En   Finetuned   Lora   Mistral   Peft   Region:us   Safetensors   Security
Model Card on HF 🤗: https://huggingface.co/rootxhacker/CodeAstra-7B 

CodeAstra 7B Benchmarks

LLME Score: 0.14518
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CodeAstra 7B (rootxhacker/CodeAstra-7B)
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CodeAstra 7B Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
Source code vulnerability detection, Security research
Applications:
Developer workflows, Code review processes, Standalone security tool
Primary Use Cases:
Identifying security vulnerabilities in source code
Limitations:
May not identify all vulnerabilities if multiple are present, Prone to false positives, Results should be verified by human experts, Affected by code complexity and context
Considerations:
Should be integrated within a broader security review process.
Supported Languages 
Go (High), Python (High), C (High), C++ (High), Fortran (High), Ruby (High), Java (High), Kotlin (High), C# (High), PHP (High), Swift (High), JavaScript (High), TypeScript (High)
Training Details 
Data Sources:
Proprietary dataset for vulnerability detection
Methodology:
Fine-tuned for vulnerability detection; trained using Parameter-Efficient Fine-Tuning (PEFT).
Hardware Used:
A100 GPUs
Input Output 
Input Format:
Programming code snippets
Accepted Modalities:
text
Output Format:
Textual analysis of vulnerabilities and quality issues
Performance Tips:
Best performance with appropriate input code snippet length.
LLM NameCodeAstra 7B
Repository 🤗https://huggingface.co/rootxhacker/CodeAstra-7B 
Model Size7b
Required VRAM0 GB
Updated2026-02-13
Maintainerrootxhacker
Model Files  0.0 GB
Supported Languagesen
Model ArchitectureAdapter
Licenseapache-2.0
Is Biasednone
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesv_proj|q_proj
LoRA Alpha16
LoRA Dropout0.05
R Param8

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Note: green Score (e.g. "73.2") means that the model is better than rootxhacker/CodeAstra-7B.

Rank the CodeAstra 7B 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 v20260328a
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