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 tatjr13/damascus-t3b-base-a-shipped# Run inference directly in the terminal:
llama cli -hf tatjr13/damascus-t3b-base-a-shippedUse 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 tatjr13/damascus-t3b-base-a-shipped# Run inference directly in the terminal:
./llama-cli -hf tatjr13/damascus-t3b-base-a-shippedBuild 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 tatjr13/damascus-t3b-base-a-shipped# Run inference directly in the terminal:
./build/bin/llama-cli -hf tatjr13/damascus-t3b-base-a-shippedUse Docker
docker model run hf.co/tatjr13/damascus-t3b-base-a-shippedQuick Links
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Check out the documentation for more information.
damascus-t3b-base-a-shipped
Untouched tpn-004 base (tpnlabs/tpn-004-base BF16, sha 5d425b36...) in the tpn-004 A layout (Q4_K_M body, Q8_0 token embedding, Q6_K output, imatrix; the 14.7 GB export /home/tim/tpn004/exports/A-im-q4km-q8e-q6o.gguf, sha 11425d78...) with the SHIPPED 305-char stripped chat template (sha 885e0c70...). DAMASCUS T3b: does cheaper compression lose Fluid points on the untouched base (vs L1 0.7193 and maxprec 0.7193)? Test artifact, not a competition entry.
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf tatjr13/damascus-t3b-base-a-shipped# Run inference directly in the terminal: llama cli -hf tatjr13/damascus-t3b-base-a-shipped