# FACET

## How to run

```bash
python main.py --full-name <hf-account-name/hf-model-name> -s <target-directory-to-save-git-clone> --enable-converter -c <path-to-python-convert-script> --enable-quantizer -q <path-to-llamacpp-quantizer> -t q4_0
```

For example,

```bash
python main.py --full-name baichuan-inc/Baichuan2-13B-Chat -s /home/ubuntu/workspace/models/ --enable-converter -c /home/ubuntu/workspace/llama.cpp/convert.py --enable-quantizer -q llama-cpp-quantizer -t Q5_K_M
```

## Allowed quantization types

```text
   2  or  Q4_0   :  3.56G, +0.2166 ppl @ LLaMA-v1-7B
   3  or  Q4_1   :  3.90G, +0.1585 ppl @ LLaMA-v1-7B
   8  or  Q5_0   :  4.33G, +0.0683 ppl @ LLaMA-v1-7B
   9  or  Q5_1   :  4.70G, +0.0349 ppl @ LLaMA-v1-7B
  10  or  Q2_K   :  2.63G, +0.6717 ppl @ LLaMA-v1-7B
  12  or  Q3_K   : alias for Q3_K_M
  11  or  Q3_K_S :  2.75G, +0.5551 ppl @ LLaMA-v1-7B
  12  or  Q3_K_M :  3.07G, +0.2496 ppl @ LLaMA-v1-7B
  13  or  Q3_K_L :  3.35G, +0.1764 ppl @ LLaMA-v1-7B
  15  or  Q4_K   : alias for Q4_K_M
  14  or  Q4_K_S :  3.59G, +0.0992 ppl @ LLaMA-v1-7B
  15  or  Q4_K_M :  3.80G, +0.0532 ppl @ LLaMA-v1-7B
  17  or  Q5_K   : alias for Q5_K_M
  16  or  Q5_K_S :  4.33G, +0.0400 ppl @ LLaMA-v1-7B
  17  or  Q5_K_M :  4.45G, +0.0122 ppl @ LLaMA-v1-7B
  18  or  Q6_K   :  5.15G, -0.0008 ppl @ LLaMA-v1-7B
   7  or  Q8_0   :  6.70G, +0.0004 ppl @ LLaMA-v1-7B
   1  or  F16    : 13.00G              @ 7B
   0  or  F32    : 26.00G              @ 7B
          COPY   : only copy tensors, no quantizing
```