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 haffner/Maestro1-9B-Heretic:
# Run inference directly in the terminal:
llama cli -hf haffner/Maestro1-9B-Heretic:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf haffner/Maestro1-9B-Heretic:
# Run inference directly in the terminal:
llama cli -hf haffner/Maestro1-9B-Heretic:
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 haffner/Maestro1-9B-Heretic:
# Run inference directly in the terminal:
./llama-cli -hf haffner/Maestro1-9B-Heretic:
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 haffner/Maestro1-9B-Heretic:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf haffner/Maestro1-9B-Heretic:
Use Docker
docker model run hf.co/haffner/Maestro1-9B-Heretic:
Quick Links

About

Heretic'ed safetensors and GGUF quants of https://huggingface.co/vectionlabs/Maestro1-9B

Multimodal Projector:

Refusals: 3/100, KL divergence: 0.0741

  • Parameters:
    • direction_index = 18.77
    • attn.o_proj.max_weight = 1.37
    • attn.o_proj.max_weight_position = 27.86
    • attn.o_proj.min_weight = 1.33
    • attn.o_proj.min_weight_distance = 18.73
    • mlp.down_proj.max_weight = 1.34
    • mlp.down_proj.max_weight_position = 22.02
    • mlp.down_proj.min_weight = 1.24
    • mlp.down_proj.min_weight_distance = 14.79
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