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Merge branch 'master' into compilade/refactor-kv-cache
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@@ -1,4 +1,4 @@
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set(TARGET imatrix)
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set(TARGET llama-imatrix)
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add_executable(${TARGET} imatrix.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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@@ -6,7 +6,7 @@ More information is available here: https://github.com/ggerganov/llama.cpp/pull/
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## Usage
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```
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./imatrix \
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./llama-imatrix \
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-m model.gguf -f some-text.txt [-o imatrix.dat] [--process-output] [--verbosity 1] \
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[--no-ppl] [--chunk 123] [--output-frequency 10] [--save-frequency 0] \
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[--in-file imatrix-prev-0.dat --in-file imatrix-prev-1.dat ...]
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@@ -25,11 +25,11 @@ For faster computation, make sure to use GPU offloading via the `-ngl` argument
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## Example
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```bash
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LLAMA_CUDA=1 make -j
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GGML_CUDA=1 make -j
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# generate importance matrix (imatrix.dat)
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./imatrix -m ggml-model-f16.gguf -f train-data.txt -ngl 99
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./llama-imatrix -m ggml-model-f16.gguf -f train-data.txt -ngl 99
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# use the imatrix to perform a Q4_K_M quantization
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./quantize --imatrix imatrix.dat ggml-model-f16.gguf ./ggml-model-q4_k_m.gguf q4_k_m
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./llama-quantize --imatrix imatrix.dat ggml-model-f16.gguf ./ggml-model-q4_k_m.gguf q4_k_m
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```
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