---
language:
- en
---

# Input files for generating the Importance Matrix

## How to quantize with an imatrix in llama.cpp

1. Get one of the input files collected here, or eleswhere.
2. Convert or download the model you want to quantise, in fp16 GGUF format.
3. Generate an imatrix file specific to the model you want to quantise
```
cd <llama.cpp directory>
./imatrix -m <model_path>/ggml-model-f16.gguf -f <matrix_training_path>/<plain_text_matrix_file> -o <output_binary_file.matrix> -t 12 -ngl 144 --chunks 100 -b 512 -c 512

# -ngl    : layers offloaded to gpu (recommended to use number of layers the model contains)
# -t 12   : number of threads (should probably match no of cpu)
# -c 512  : context size, testing seems to show 512 is recommended (default=512, 0=loaded from model)
# -b 200  : batch size (default=512)
# --chunks 100 (recommended)
# --mlock : keep model in ram (only use if you had sufficient RAM for the whole fp16)
```
4. Use the generated binary matrix file to quantise the model
```
./quantize <model_path>/ggml-model-f16.gguf -matrix <matrix_file> <output_model_path>/ggml-model-IQ4_XS.gguf IQ4_XS
```
Note: normal quantisation also benefits from using a matrix file. It also seem that a larger input data is
better for higher quantisation.