8648c52101
* make : deprecate ggml-ci * ci : disable Makefile builds ggml-ci * docs : remove make references [no ci] * ci : disable swift build ggml-ci * docs : remove obsolete make references, scripts, examples ggml-ci * basic fix for compare-commits.sh * update build.md * more build.md updates * more build.md updates * more build.md updates * Update Makefile Co-authored-by: Diego Devesa <slarengh@gmail.com> --------- Co-authored-by: slaren <slarengh@gmail.com>
33 lines
2 KiB
Markdown
33 lines
2 KiB
Markdown
# llama.cpp/examples/imatrix
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Compute an importance matrix for a model and given text dataset. Can be used during quantization to enchance the quality of the quantized models.
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More information is available here: https://github.com/ggerganov/llama.cpp/pull/4861
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## Usage
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```
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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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```
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Here `-m` with a model name and `-f` with a file containing training data (such as e.g. `wiki.train.raw`) are mandatory.
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The parameters in square brackets are optional and have the following meaning:
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* `-o` (or `--output-file`) specifies the name of the file where the computed data will be stored. If missing `imatrix.dat` is used.
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* `--verbosity` specifies the verbosity level. If set to `0`, no output other than the perplexity of the processed chunks will be generated. If set to `1`, each time the results are saved a message is written to `stderr`. If `>=2`, a message is output each time data is collected for any tensor. Default verbosity level is `1`.
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* `--output-frequency` specifies how often the so far computed result is saved to disk. Default is 10 (i.e., every 10 chunks)
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* `--save-frequency` specifies how often to save a copy of the imatrix in a separate file. Default is 0 (i.e., never)
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* `--process-output` specifies if data will be collected for the `output.weight` tensor. My experience is that it is better to not utilize the importance matrix when quantizing `output.weight`, so this is set to `false` by default.
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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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# generate importance matrix (imatrix.dat)
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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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./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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