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 ggml-org/tinyopenjev-for-testing-gguf:Q8_0
# Run inference directly in the terminal:
llama cli -hf ggml-org/tinyopenjev-for-testing-gguf:Q8_0
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ggml-org/tinyopenjev-for-testing-gguf:Q8_0
# Run inference directly in the terminal:
llama cli -hf ggml-org/tinyopenjev-for-testing-gguf:Q8_0
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 ggml-org/tinyopenjev-for-testing-gguf:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf ggml-org/tinyopenjev-for-testing-gguf:Q8_0
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 ggml-org/tinyopenjev-for-testing-gguf:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ggml-org/tinyopenjev-for-testing-gguf:Q8_0
Use Docker
docker model run hf.co/ggml-org/tinyopenjev-for-testing-gguf:Q8_0
Quick Links

tinyopenjev-for-testing-gguf

Q8_0 GGUF (text model + mmproj) of a very small slice of openjev/openjev, for testing purposes only.

The slice keeps the first 4 of 64 text layers and the first 2 of 27 vision blocks, and also cuts the width (hidden size 5120 -> 64, fewer attention heads, smaller FFN). About 34M parameters, most of them in the token embedding and output matrices.

The output is not meaningful. Do not use this model for anything other than testing a loader or a runtime.

OpenJev weights are released under CC BY-NC 4.0 and are derived from Qwen/Qwen3.8-27B (Apache 2.0); see NOTICE, LICENSE and LICENSE-APACHE-2.0.

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