Patch 1 (microsoft#27)

update from VPTQ community

README.md

@@ -33,7 +33,9 @@ VPTQ achieves better accuracy and higher throughput with lower quantization over
 | LLaMA-2 70B | 2.07     | 3.93 | 5.72 | 68.6   | 9.7    | 19.54   | 19      |
 |             | 2.11     | 3.92 | 5.71 | 68.7   | 9.7    | 20.01   | 19      |
 
-## Installation and Evaluation
+---
+
+## Installation
 
 ### Dependencies
 
@@ -55,6 +57,7 @@ export PATH=/usr/local/cuda-12/bin/:$PATH  # set dependent on your environment
 pip install git+https://github.com/microsoft/VPTQ.git --no-build-isolation
 ```
 
+## Evaluation
 ### Models from Open Source Community
 
 ⚠️ The repository only provides a method of model quantization algorithm. 
@@ -63,13 +66,30 @@ pip install git+https://github.com/microsoft/VPTQ.git --no-build-isolation
 
 ⚠️ The repository cannot guarantee the performance of those models.
 
-|      Model Series      | Collections |
-|:----------------------:|:-----------:|
-|  Llama 3.1 8B Instruct |     [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-llama-31-8b-instruct-without-finetune-66f2b70b1d002ceedef02d2e)    |
-| Llama 3.1 70B Instruct |     [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-llama-31-70b-instruct-without-finetune-66f2bf454d3dd78dfee2ff11)    |
-|  Qwen 2.5 7B Instruct  |     [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-qwen-25-7b-instruct-without-finetune-66f3e9866d3167cc05ce954a)    |
-|  Qwen 2.5 72B Instruct |     [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-qwen-25-72b-instruct-without-finetune-66f3bf1b3757dfa1ecb481c0)    |
-|  Qwen 2.5 405B Instruct |     [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-llama-31-405b-instruct-without-finetune-66f4413f9ba55e1a9e52cfb0)    |
+
+**Quick Estimation of Model Bitwidth (Excluding Codebook Overhead)**:
+- **Model Naming Convention**: The model's name includes the **vector length** $v$, **codebook (lookup table) size**, and **residual codebook size**. For example, "Meta-Llama-3.1-70B-Instruct-v8-k65536-256-woft" and "Meta-Llama-3.1-70B-Instruct", where:
+  - **Vector Length**: 8
+  - **Number of Centroids**: 65536 (2^16)
+  - **Number of Residual Centroids**: 256 (2^8)
+- **Equivalent Bitwidth Calculation**:
+  - **Index**: log2(65536) = 16 / 8 = 2 bits
+  - **Residual Index**: log2(256) = 8 / 8 = 1 bit
+  - **Total Bitwidth**: 2 + 1 = 3 bits
+- **Model Size Estimation**: 70B * 3 bits / 8 bits per Byte = 26.25 GB
+
+- **Note**: This estimate does not include the size of the codebook (lookup table), other parameter overheads, and the padding overhead for storing indices. For the detailed calculation method, please refer to **Tech Report Appendix C.2**.
+
+
+|      Model Series      | Collections |  (Estimated) Bit per weight |
+|:----------------------:|:-----------:| ----------------------------|
+|  Llama 3.1 8B Instruct   | [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-llama-31-8b-instruct-without-finetune-66f2b70b1d002ceedef02d2e)    | [4 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-8B-Instruct-v8-k65536-65536-woft) [3.5 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-8B-Instruct-v8-k65536-4096-woft) [3 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-8B-Instruct-v8-k65536-256-woft) [2.3 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-8B-Instruct-v12-k65536-4096-woft) |
+|  Llama 3.1 70B Instruct  | [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-llama-31-70b-instruct-without-finetune-66f2bf454d3dd78dfee2ff11)   | [4 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-70B-Instruct-v8-k65536-65536-woft) [3 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-70B-Instruct-v8-k65536-256-woft) [2.25 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-70B-Instruct-v8-k65536-4-woft)  [2 bits (1)](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-70B-Instruct-v16-k65536-65536-woft) [2 bits (2)](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-70B-Instruct-v8-k65536-0-woft) [1.93 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-70B-Instruct-v16-k65536-32768-woft) [1.875 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-70B-Instruct-v8-k32768-0-woft) [1.75 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-70B-Instruct-v8-k16384-0-woft) |
+|  Llama 3.1 405B Instruct | [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-llama-31-405b-instruct-without-finetune-66f4413f9ba55e1a9e52cfb0)  | [1.875 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-405B-Instruct-v16-k32768-32768-woft) [1.625 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-405B-Instruct-v16-k65536-1024-woft) [1.5 bits (1)](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-405B-Instruct-v8-k4096-0-woft) [1.5 bits (2)](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-405B-Instruct-v16-k65536-256-woft) [1.43 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-405B-Instruct-v16-k65536-128-woft) [1.375 bits](https://huggingface.co/VPTQ-community/Meta-Llama-3.1-405B-Instruct-v16-k65536-64-woft)|
+|  Qwen 2.5 7B Instruct    | [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-qwen-25-7b-instruct-without-finetune-66f3e9866d3167cc05ce954a)     | [4 bits](https://huggingface.co/VPTQ-community/Qwen2.5-7B-Instruct-v8-k65536-65536-woft) [3 bits](https://huggingface.co/VPTQ-community/Qwen2.5-7B-Instruct-v8-k65536-256-woft) [2 bits (1)](https://huggingface.co/VPTQ-community/Qwen2.5-7B-Instruct-v8-k256-256-woft) [2 bits (2)](https://huggingface.co/VPTQ-community/Qwen2.5-7B-Instruct-v8-k65536-0-woft)  [2 bits (3)](https://huggingface.co/VPTQ-community/Qwen2.5-7B-Instruct-v16-k65536-65536-woft)  |
+|  Qwen 2.5 14B Instruct   | [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-qwen-25-14b-instruct-without-finetune-66f827f83c7ffa7931b8376c)    | [4 bits](https://huggingface.co/VPTQ-community/Qwen2.5-14B-Instruct-v8-k65536-65536-woft) [3 bits](https://huggingface.co/VPTQ-community/Qwen2.5-14B-Instruct-v8-k65536-256-woft) [2 bits (1)](https://huggingface.co/VPTQ-community/Qwen2.5-14B-Instruct-v8-k256-256-woft) [2 bits (2)](https://huggingface.co/VPTQ-community/Qwen2.5-14B-Instruct-v8-k65536-0-woft)  [2 bits (3)](https://huggingface.co/VPTQ-community/Qwen2.5-14B-Instruct-v16-k65536-65536-woft)  |
+|  Qwen 2.5 72B Instruct   | [HF 🤗](https://huggingface.co/collections/VPTQ-community/vptq-qwen-25-72b-instruct-without-finetune-66f3bf1b3757dfa1ecb481c0)    | [4 bits](https://huggingface.co/VPTQ-community/Qwen2.5-72B-Instruct-v8-k65536-65536-woft) [3 bits](https://huggingface.co/VPTQ-community/Qwen2.5-72B-Instruct-v8-k65536-256-woft) [2.38 bits](https://huggingface.co/VPTQ-community/Qwen2.5-72B-Instruct-v8-k1024-512-woft) [2.25 bits (1)](https://huggingface.co/VPTQ-community/Qwen2.5-72B-Instruct-v8-k512-512-woft) [2.25 bits (2)](https://huggingface.co/VPTQ-community/Qwen2.5-72B-Instruct-v8-k65536-4-woft) [2 bits (1)](https://huggingface.co/VPTQ-community/Qwen2.5-72B-Instruct-v8-k65536-0-woft) [2 bits (2)](https://huggingface.co/VPTQ-community/Qwen2.5-72B-Instruct-v16-k65536-65536-woft) [1.94 bits](https://huggingface.co/VPTQ-community/Qwen2.5-72B-Instruct-v16-k65536-32768-woft) |
+
 
 ### Language Generation Example
 To generate text using the pre-trained model, you can use the following code snippet:
@@ -113,6 +133,7 @@ A environment variable is available to control share link or not.
 python -m vptq.app
 ```
 
+---
 
 ## Road Map
 - [ ] Merge the quantization algorithm into the public repository.
@@ -150,6 +171,8 @@ EMNLP 2024 Main
 }
 ```
 
+---
+
 ## Limitation of VPTQ
 * ⚠️ VPTQ should only be used for research and experimental purposes. Further testing and validation are needed before you use it.
 * ⚠️ The repository only provides a method of model quantization algorithm. The open-source community may provide models based on the technical report and quantization algorithm by themselves, but the repository cannot guarantee the performance of those models.