README.md

---
license: apache-2.0
base_model: lmzheng/grok-1
---


# Grok-1-W4A8KV8
## Introduction
  This model was created by applying [Quark](https://quark.docs.amd.com/latest/index.html) with calibration samples from Pile dataset.
## Quantization Stragegy
  - ***Quantized Layers***: All linear layers excluding "lm_head", "*.gate"
  - ***Weight***: FP8 symmetric per-tensor, additionally, INT4 symmetric per-channel for MoE linear
  - ***Activation***: FP8 symmetric per-tensor
  - ***KV Cache***: FP8 symmetric per-tensor
### INT4 Packing
Every eight `int4` values are packed into a single `int32` integeter following the sequence defined by `order_map = [0, 2, 4, 6, 1, 3, 5, 7]`.
## Quick Start
1. [Download and install Quark](https://quark.docs.amd.com/latest/install.html)
2. Run the quantization script in the example folder using the following command line:
```sh
export MODEL_DIR = [local model checkpoint folder] or lmzheng/grok-1 
python3 quantize_quark.py \
        --model_dir $MODEL_DIR \
        --output_dir grok-1-W4A8KV8 \
        --quant_scheme TBD \
        --kv_cache_dtype fp8 \
        --num_calib_data 128 \
        --model_export hf_format \
        --multi_gpu \
        --custom_mode fp8
```
## Deployment
Quark has its own export format and allows FP8 quantized models to be efficiently deployed using the SGLang backend.
## Evaluation

#### Evaluation scores
<table>
  <tr>
   <td><strong>Benchmark</strong>
   </td>
   <td><strong>grok-1 </strong>
   </td>
   <td><strong>grok-1-W4A8KV8(this model)</strong>
   </td>
  </tr>
  <tr>
   <td>gsm8k
   </td>
   <td>0.821
   </td>
   <td>0.817
   </td>
  </tr>
</table>

#### License
Modifications copyright(c) 2024 Advanced Micro Devices,Inc. All rights reserved.