|
|
|
--- |
|
license: mit |
|
language: |
|
- en |
|
pipeline_tag: text-generation |
|
--- |
|
|
|
ZeroWw 'SILLY' version. |
|
The original model has been quantized (fq8 version) |
|
and a percentage of it's tensors have |
|
been modified adding some noise. |
|
|
|
Full colab: https://colab.research.google.com/drive/1a7seagBzu5l3k3FL4SFk0YJocl7nsDJw?usp=sharing |
|
|
|
Fast colab: https://colab.research.google.com/drive/1SDD7ox21di_82Y9v68AUoy0PhkxwBVvN?usp=sharing |
|
|
|
Original reddit post: https://www.reddit.com/r/LocalLLaMA/comments/1ec0s8p/i_made_a_silly_test/ |
|
|
|
I created a program to randomize the weights of a model. The program has 2 parameters: the percentage of weights to modify and the percentage of the original value to randmly apply to each weight. |
|
|
|
At the end I check the resulting GGUF file for binary differences. |
|
In this example I set to modify 100% of the weights of the original model by a maximum of 15% deviation. |
|
|
|
Since the deviation is calculated on the F32 weights, when quantized to Q8\_0 this changes. |
|
So, in the end I got a file that compared to the original has: |
|
|
|
Bytes Difference percentage: 73.04% |
|
|
|
Average value divergence: 2.98% |
|
|
|
The cool thing is that chatting with the model I see no apparent difference and the model still works nicely as the original. |
|
|
|
Since I am running everything on CPU, I could not run perplexity scores or anything computing intensive. |
|
|
|
As a small test, I asked the model a few questions (like the history of the roman empire) and then fact check its answer using a big model. No errors were detected. |
|
|
|
Update: all procedure tested and created on COLAB. |
|
|
|
Created on: Sat Jul 27, 15:51:17 |
|
|