chore: comment out llama.cpp build in setup.sh
This commit is contained in:
Roland Tannous
parent
40c5b86005
commit
91e90a256c
1 changed files with 130 additions and 127 deletions
257
studio/setup.sh
257
studio/setup.sh
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@ -275,133 +275,136 @@ else
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fi
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# ── 8. Build llama.cpp binaries for GGUF inference + export ──
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# Builds at ~/.unsloth/llama.cpp — a single shared location under the user's
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# home directory. This is used by both the inference server and the GGUF
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# export pipeline (unsloth-zoo).
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# - llama-server: for GGUF model inference
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# - llama-quantize: for GGUF export quantization (symlinked to root for check_llama_cpp())
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UNSLOTH_HOME="$HOME/.unsloth"
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mkdir -p "$UNSLOTH_HOME"
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LLAMA_CPP_DIR="$UNSLOTH_HOME/llama.cpp"
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LLAMA_SERVER_BIN="$LLAMA_CPP_DIR/build/bin/llama-server"
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rm -rf "$LLAMA_CPP_DIR"
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{
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# Check prerequisites
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if ! command -v cmake &>/dev/null; then
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echo ""
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echo "⚠️ cmake not found — skipping llama-server build (GGUF inference won't be available)"
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echo " Install cmake and re-run setup.sh to enable GGUF inference."
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elif ! command -v git &>/dev/null; then
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echo ""
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echo "⚠️ git not found — skipping llama-server build (GGUF inference won't be available)"
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else
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echo ""
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echo "Building llama-server for GGUF inference..."
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BUILD_OK=true
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run_quiet "clone llama.cpp" git clone --depth 1 https://github.com/ggml-org/llama.cpp.git "$LLAMA_CPP_DIR" || BUILD_OK=false
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if [ "$BUILD_OK" = true ]; then
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# Skip tests/examples we don't need (faster build)
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CMAKE_ARGS="-DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_NATIVE=ON"
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# Use ccache if available (dramatically faster rebuilds)
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if command -v ccache &>/dev/null; then
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CMAKE_ARGS="$CMAKE_ARGS -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_CUDA_COMPILER_LAUNCHER=ccache"
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echo " Using ccache for faster compilation"
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fi
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# Detect CUDA: check nvcc on PATH, then common install locations
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NVCC_PATH=""
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if command -v nvcc &>/dev/null; then
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NVCC_PATH="$(command -v nvcc)"
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elif [ -x /usr/local/cuda/bin/nvcc ]; then
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NVCC_PATH="/usr/local/cuda/bin/nvcc"
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export PATH="/usr/local/cuda/bin:$PATH"
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elif ls /usr/local/cuda-*/bin/nvcc &>/dev/null 2>&1; then
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# Pick the newest cuda-XX.X directory
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NVCC_PATH="$(ls -d /usr/local/cuda-*/bin/nvcc 2>/dev/null | sort -V | tail -1)"
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export PATH="$(dirname "$NVCC_PATH"):$PATH"
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fi
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if [ -n "$NVCC_PATH" ]; then
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echo " Building with CUDA support (nvcc: $NVCC_PATH)..."
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CMAKE_ARGS="$CMAKE_ARGS -DGGML_CUDA=ON"
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# Detect GPU compute capability and limit CUDA architectures
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# Without this, cmake builds for ALL default archs (very slow)
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CUDA_ARCHS=""
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if command -v nvidia-smi &>/dev/null; then
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# Read all GPUs, deduplicate (handles mixed-GPU hosts)
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_raw_caps=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader 2>/dev/null || true)
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while IFS= read -r _cap; do
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_cap=$(echo "$_cap" | tr -d '[:space:]')
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if [[ "$_cap" =~ ^([0-9]+)\.([0-9]+)$ ]]; then
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_arch="${BASH_REMATCH[1]}${BASH_REMATCH[2]}"
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# Append if not already present
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case ";$CUDA_ARCHS;" in
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*";$_arch;"*) ;;
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*) CUDA_ARCHS="${CUDA_ARCHS:+$CUDA_ARCHS;}$_arch" ;;
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esac
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fi
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done <<< "$_raw_caps"
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fi
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if [ -n "$CUDA_ARCHS" ]; then
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echo " GPU compute capabilities: ${CUDA_ARCHS//;/, } -- limiting build to detected archs"
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CMAKE_ARGS="$CMAKE_ARGS -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCHS}"
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else
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echo " Could not detect GPU arch -- building for all default CUDA architectures (slower)"
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fi
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# Multi-threaded nvcc compilation (uses all CPU cores per .cu file)
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CMAKE_ARGS="$CMAKE_ARGS -DCMAKE_CUDA_FLAGS=--threads=0"
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elif [ -d /usr/local/cuda ] || nvidia-smi &>/dev/null; then
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echo " CUDA driver detected but nvcc not found — building CPU-only"
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echo " To enable GPU: install cuda-toolkit or add nvcc to PATH"
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else
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echo " Building CPU-only (no CUDA detected)..."
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fi
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NCPU=$(nproc 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || echo 4)
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# Use Ninja if available (faster parallel builds than Make)
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CMAKE_GENERATOR_ARGS=""
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if command -v ninja &>/dev/null; then
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CMAKE_GENERATOR_ARGS="-G Ninja"
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fi
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run_quiet "cmake llama.cpp" cmake $CMAKE_GENERATOR_ARGS -S "$LLAMA_CPP_DIR" -B "$LLAMA_CPP_DIR/build" $CMAKE_ARGS || BUILD_OK=false
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fi
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if [ "$BUILD_OK" = true ]; then
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run_quiet "build llama-server" cmake --build "$LLAMA_CPP_DIR/build" --config Release --target llama-server -j"$NCPU" || BUILD_OK=false
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fi
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# Also build llama-quantize (needed by unsloth-zoo's GGUF export pipeline)
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if [ "$BUILD_OK" = true ]; then
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run_quiet "build llama-quantize" cmake --build "$LLAMA_CPP_DIR/build" --config Release --target llama-quantize -j"$NCPU" || true
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# Symlink to llama.cpp root — check_llama_cpp() looks for the binary there
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QUANTIZE_BIN="$LLAMA_CPP_DIR/build/bin/llama-quantize"
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if [ -f "$QUANTIZE_BIN" ]; then
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ln -sf build/bin/llama-quantize "$LLAMA_CPP_DIR/llama-quantize"
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fi
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fi
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if [ "$BUILD_OK" = true ]; then
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if [ -f "$LLAMA_SERVER_BIN" ]; then
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echo "✅ llama-server built at $LLAMA_SERVER_BIN"
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else
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echo "⚠️ llama-server binary not found after build — GGUF inference won't be available"
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fi
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if [ -f "$LLAMA_CPP_DIR/llama-quantize" ]; then
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echo "✅ llama-quantize available for GGUF export"
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fi
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else
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echo "⚠️ llama-server build failed — GGUF inference won't be available, but everything else works"
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fi
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fi
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}
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# Disabled: llama.cpp build is commented out for now.
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# UNCOMMENT the block below to re-enable.
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#
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# # Builds at ~/.unsloth/llama.cpp — a single shared location under the user's
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# # home directory. This is used by both the inference server and the GGUF
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# # export pipeline (unsloth-zoo).
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# # - llama-server: for GGUF model inference
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# # - llama-quantize: for GGUF export quantization (symlinked to root for check_llama_cpp())
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# UNSLOTH_HOME="$HOME/.unsloth"
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# mkdir -p "$UNSLOTH_HOME"
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# LLAMA_CPP_DIR="$UNSLOTH_HOME/llama.cpp"
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# LLAMA_SERVER_BIN="$LLAMA_CPP_DIR/build/bin/llama-server"
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# rm -rf "$LLAMA_CPP_DIR"
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# {
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# # Check prerequisites
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# if ! command -v cmake &>/dev/null; then
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# echo ""
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# echo "⚠️ cmake not found — skipping llama-server build (GGUF inference won't be available)"
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# echo " Install cmake and re-run setup.sh to enable GGUF inference."
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# elif ! command -v git &>/dev/null; then
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# echo ""
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# echo "⚠️ git not found — skipping llama-server build (GGUF inference won't be available)"
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# else
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# echo ""
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# echo "Building llama-server for GGUF inference..."
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#
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# BUILD_OK=true
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# run_quiet "clone llama.cpp" git clone --depth 1 https://github.com/ggml-org/llama.cpp.git "$LLAMA_CPP_DIR" || BUILD_OK=false
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#
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# if [ "$BUILD_OK" = true ]; then
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# # Skip tests/examples we don't need (faster build)
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# CMAKE_ARGS="-DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_SERVER=ON -DGGML_NATIVE=ON"
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#
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# # Use ccache if available (dramatically faster rebuilds)
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# if command -v ccache &>/dev/null; then
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# CMAKE_ARGS="$CMAKE_ARGS -DCMAKE_C_COMPILER_LAUNCHER=ccache -DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_CUDA_COMPILER_LAUNCHER=ccache"
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# echo " Using ccache for faster compilation"
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# fi
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#
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# # Detect CUDA: check nvcc on PATH, then common install locations
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# NVCC_PATH=""
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# if command -v nvcc &>/dev/null; then
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# NVCC_PATH="$(command -v nvcc)"
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# elif [ -x /usr/local/cuda/bin/nvcc ]; then
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# NVCC_PATH="/usr/local/cuda/bin/nvcc"
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# export PATH="/usr/local/cuda/bin:$PATH"
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# elif ls /usr/local/cuda-*/bin/nvcc &>/dev/null 2>&1; then
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# # Pick the newest cuda-XX.X directory
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# NVCC_PATH="$(ls -d /usr/local/cuda-*/bin/nvcc 2>/dev/null | sort -V | tail -1)"
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# export PATH="$(dirname "$NVCC_PATH"):$PATH"
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# fi
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#
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# if [ -n "$NVCC_PATH" ]; then
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# echo " Building with CUDA support (nvcc: $NVCC_PATH)..."
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# CMAKE_ARGS="$CMAKE_ARGS -DGGML_CUDA=ON"
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#
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# # Detect GPU compute capability and limit CUDA architectures
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# # Without this, cmake builds for ALL default archs (very slow)
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# CUDA_ARCHS=""
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# if command -v nvidia-smi &>/dev/null; then
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# # Read all GPUs, deduplicate (handles mixed-GPU hosts)
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# _raw_caps=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader 2>/dev/null || true)
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# while IFS= read -r _cap; do
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# _cap=$(echo "$_cap" | tr -d '[:space:]')
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# if [[ "$_cap" =~ ^([0-9]+)\.([0-9]+)$ ]]; then
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# _arch="${BASH_REMATCH[1]}${BASH_REMATCH[2]}"
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# # Append if not already present
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# case ";$CUDA_ARCHS;" in
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# *";$_arch;"*) ;;
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# *) CUDA_ARCHS="${CUDA_ARCHS:+$CUDA_ARCHS;}$_arch" ;;
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# esac
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# fi
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# done <<< "$_raw_caps"
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# fi
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#
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# if [ -n "$CUDA_ARCHS" ]; then
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# echo " GPU compute capabilities: ${CUDA_ARCHS//;/, } -- limiting build to detected archs"
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# CMAKE_ARGS="$CMAKE_ARGS -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCHS}"
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# else
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# echo " Could not detect GPU arch -- building for all default CUDA architectures (slower)"
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# fi
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#
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# # Multi-threaded nvcc compilation (uses all CPU cores per .cu file)
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# CMAKE_ARGS="$CMAKE_ARGS -DCMAKE_CUDA_FLAGS=--threads=0"
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# elif [ -d /usr/local/cuda ] || nvidia-smi &>/dev/null; then
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# echo " CUDA driver detected but nvcc not found — building CPU-only"
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# echo " To enable GPU: install cuda-toolkit or add nvcc to PATH"
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# else
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# echo " Building CPU-only (no CUDA detected)..."
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# fi
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#
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# NCPU=$(nproc 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || echo 4)
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#
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# # Use Ninja if available (faster parallel builds than Make)
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# CMAKE_GENERATOR_ARGS=""
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# if command -v ninja &>/dev/null; then
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# CMAKE_GENERATOR_ARGS="-G Ninja"
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# fi
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#
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# run_quiet "cmake llama.cpp" cmake $CMAKE_GENERATOR_ARGS -S "$LLAMA_CPP_DIR" -B "$LLAMA_CPP_DIR/build" $CMAKE_ARGS || BUILD_OK=false
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# fi
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#
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# if [ "$BUILD_OK" = true ]; then
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# run_quiet "build llama-server" cmake --build "$LLAMA_CPP_DIR/build" --config Release --target llama-server -j"$NCPU" || BUILD_OK=false
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# fi
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#
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# # Also build llama-quantize (needed by unsloth-zoo's GGUF export pipeline)
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# if [ "$BUILD_OK" = true ]; then
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# run_quiet "build llama-quantize" cmake --build "$LLAMA_CPP_DIR/build" --config Release --target llama-quantize -j"$NCPU" || true
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# # Symlink to llama.cpp root — check_llama_cpp() looks for the binary there
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# QUANTIZE_BIN="$LLAMA_CPP_DIR/build/bin/llama-quantize"
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# if [ -f "$QUANTIZE_BIN" ]; then
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# ln -sf build/bin/llama-quantize "$LLAMA_CPP_DIR/llama-quantize"
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# fi
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# fi
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#
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# if [ "$BUILD_OK" = true ]; then
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# if [ -f "$LLAMA_SERVER_BIN" ]; then
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# echo "✅ llama-server built at $LLAMA_SERVER_BIN"
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# else
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# echo "⚠️ llama-server binary not found after build — GGUF inference won't be available"
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# fi
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# if [ -f "$LLAMA_CPP_DIR/llama-quantize" ]; then
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# echo "✅ llama-quantize available for GGUF export"
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# fi
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# else
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# echo "⚠️ llama-server build failed — GGUF inference won't be available, but everything else works"
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# fi
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# fi
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# }
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echo ""
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if [ "$IS_COLAB" = true ]; then
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