How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf anyalkonsafe/evilguy4:F16# Run inference directly in the terminal:
llama cli -hf anyalkonsafe/evilguy4:F16Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf anyalkonsafe/evilguy4:F16# Run inference directly in the terminal:
./build/bin/llama cli -hf anyalkonsafe/evilguy4:F16Use Docker
docker model run hf.co/anyalkonsafe/evilguy4:F16Quick Links
evilguy4
The newest evilguy. Now based off Gemma4 E4B.
Changes
- Better at math
- Trained to handle more slang/substitutions/typos (hllo, ello, or complete gibberish)
- Fixed a bunch of weird hallucinations
Recommended sampling: temperature 1.0, top_p 0.95, top_k 64.
Usage
llama-server -m evilguy4-q4-k-m.gguf --jinja
Run the llama.cpp server with --jinja so the embedded chat template (and tool calling) is used.
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Hardware compatibility
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Model tree for anyalkonsafe/evilguy4
Base model
google/gemma-4-E4B Finetuned
google/gemma-4-E4B-it Quantized
unsloth/gemma-4-E4B-it-unsloth-bnb-4bit
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf anyalkonsafe/evilguy4:F16# Run inference directly in the terminal: llama cli -hf anyalkonsafe/evilguy4:F16