How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf enosislabs/aether-2b-cyber-gguf:
# Run inference directly in the terminal:
llama cli -hf enosislabs/aether-2b-cyber-gguf:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf enosislabs/aether-2b-cyber-gguf:
# Run inference directly in the terminal:
llama cli -hf enosislabs/aether-2b-cyber-gguf:
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf enosislabs/aether-2b-cyber-gguf:
# Run inference directly in the terminal:
./llama-cli -hf enosislabs/aether-2b-cyber-gguf:
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf enosislabs/aether-2b-cyber-gguf:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf enosislabs/aether-2b-cyber-gguf:
Use Docker
docker model run hf.co/enosislabs/aether-2b-cyber-gguf:
Quick Links

EnosisLabs enosislabs-aether-2b-cyber GGUF

Generated UTC: 2026-06-21T06:52:20.706093+00:00 Source Transformers repo: enosislabs/aether-2b-cyber

GGUF deployment artifacts. Each quant lives in its own folder.

Quant Layout

  • q2_k
  • q4_k_m
  • q5_k_m
  • q8_0

Quant Semantics

  • q2_k/: smallest, lowest memory, lowest fidelity.
  • q4_k_m/: balanced low-power default.
  • q5_k_m/: higher quality, more memory.
  • q8_0/: largest, highest fidelity among generated GGUF files.

llama.cpp

./llama-cli \
  -m q4_k_m/enosislabs-aether-2b-cyber.Q4_K_M.gguf \
  -p "<|im_start|>user\nAnalyze this finding.<|im_end|>\n<|im_start|>assistant\n"

Usage Rider

Intended only for authorized security testing, defensive engineering, internal red-team labs, and purple-team education.

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Architecture
qwen35
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