llama.cpp/examples/falcon_quantize/CMakeLists.txt

set(TARGET falcon_quantize)
add_executable(${TARGET} quantize.cpp)
target_link_libraries(${TARGET} PRIVATE libfalcon ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
if(TARGET BUILD_INFO)
  add_dependencies(${TARGET} BUILD_INFO)
endif()
Work in progress. Added falcon main and library based on llama.cpp CPU inference works (getting ~260ms/token on 7B 16 bit falcon) Tested with 7B 16 bit and the two shakespear models (both in 16 bit precisiononly) TODO/WIP: 1) quantization runs, creates a ggjt 3 file but something is wrong with the quantized model binary - even quantization from 16 -> 16 also fails, something is wrong in the tensors produced 2) mmap should work with quantized binaries once 1) is solved 3) CUDA support is mostly there, it's currently disabled (all CPU backend) 4) memory/context caluculations are off, GPU memory calculations are wrong either 5) the python conversion script is pre GGML 1 version (tokens without scores) 6) some stuff is still called "llama", some of it should be renamed to a generic name as it works for both 7) the GGML produced by the current python uses an old ftype method Makfiles: cmake on windows with build tools works the makefile for linux/msys was blind adjusted but not tested yet - possibly missed something Changes to the codebase: * repeat2 has been added to ggml (jploski - https://github.com/ggerganov/ggml/pull/231) including the backward variant (untested, probably fails) * minor changes to work with falcon (name length) * libfalcon is the previous "llama.cpp" and falcon_main is the previous main.cpp 2023-06-16 14:31:02 +00:00			`set(TARGET falcon_quantize)`
			`add_executable(${TARGET} quantize.cpp)`
			`target_link_libraries(${TARGET} PRIVATE libfalcon ${CMAKE_THREAD_LIBS_INIT})`
			`target_compile_features(${TARGET} PRIVATE cxx_std_11)`
			`if(TARGET BUILD_INFO)`
			`add_dependencies(${TARGET} BUILD_INFO)`
			`endif()`