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Aegis1.2 C 7b model by polzdgl
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Model

Aegis1.2 C 7b

by polzdgl polzdgl/aegis1.2-c-7b
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 99
Q: Quality 65
Tech Context
7 Params
32.768K Ctx
Vital Performance —
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
7B Params
32k Context
0 Downloads
8G GPU ~8GB Est. VRAM
Dense QWEN2FORCAUSALLM Architecture
Model Information Summary
Entity Passport
Registry ID polzdgl/aegis1.2-c-7b
Provider huggingface
πŸ’Ύ

Compute Threshold

~7.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{polzdgl_aegis1_2_c_7b,
  author = {polzdgl},
  title = {Aegis1.2 C 7b Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/polzdgl/aegis1.2-c-7b}},
  note = {Accessed via Free2AITools.}
}
APA Style
polzdgl. (2026). Aegis1.2 C 7b [Model]. Free2AITools. https://huggingface.co/polzdgl/aegis1.2-c-7b

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run aegis1.2-c-7b
πŸ€— HF Download
huggingface-cli download polzdgl/aegis1.2-c-7b

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 0
Recency (R) 99
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Aegis1.2 C 7b: Authority (A:0), Popularity (P:0), Recency (R:99), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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⚠️ 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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πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--polzdgl--aegis1.2-c-7b
slug
polzdgl--aegis1.2-c-7b
source
huggingface
author
polzdgl
tags
gguf, qwen2, llama.cpp, llama-cpp, unsloth, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

architecture
Qwen2ForCausalLM
params billions
7
context length
32,768
vram gb
7.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
0

Data indexed from public sources. Updated daily.