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 AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
# Run inference directly in the terminal:
llama cli -hf AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
# Run inference directly in the terminal:
llama cli -hf AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
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 AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
# Run inference directly in the terminal:
./llama-cli -hf AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
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 AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
Use Docker
docker model run hf.co/AetherArchitectural/EXAONE-3.5-7.8B-Instruct-abliterated-GGUF-ARM-Imatrix-Community:
Quick Links
aetherarchio-flat-banner Check Community Request - #82 for details.

Model name:
EXAONE-3.5-2.4B-Instruct-abliterated

Model link:
https://huggingface.co/huihui-ai/EXAONE-3.5-7.8B-Instruct-abliterated

[huihui-ai]
"This is an uncensored version of LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens."

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Architecture
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