🧠
Cybersec Gemma Merged model by XChava
⭐ 37
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Model

Cybersec Gemma Merged

by XChava hf-model--xchava--cybersec-gemma-merged
Nexus Index
37.0 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 97
Q: Quality 65
Tech Context
Vital Performance
0 DL / 30D
0.0%
Source →
Audited 37 FNI Score
Tiny - Params
- Context
0 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--xchava--cybersec-gemma-merged
License Apache-2.0
Provider huggingface
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Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__xchava__cybersec_gemma_merged,
  author = {XChava},
  title = {Cybersec Gemma Merged Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/xchava/cybersec-gemma-merged}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
XChava. (2026). Cybersec Gemma Merged [Model]. Free2AITools. https://huggingface.co/xchava/cybersec-gemma-merged

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download xchava/cybersec-gemma-merged
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
37.0
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 97
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Cybersec Gemma Merged: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:97), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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Technical Deep Dive

Uploaded finetuned model

  • Developed by: XChava
  • License: apache-2.0
  • Finetuned from model : unsloth/gemma-4-E2B-it

This gemma4 model was trained 2x faster with Unsloth and Huggingface's TRL library.

⚠ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

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📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--xchava--cybersec-gemma-merged
slug
xchava--cybersec-gemma-merged
source
huggingface
author
XChava
license
Apache-2.0
tags
transformers, safetensors, gemma4, image-text-to-text, text-generation-inference, unsloth, conversational, en, base_model:unsloth/gemma-4-e2b-it, base_model:finetune:unsloth/gemma-4-e2b-it, license:apache-2.0, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
image-text-to-text

📊 Engagement & Metrics

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