All credits belong to the author.
It stands for
Importance Matrix, a technique used to improve the quality of quantized models.
[1]
The
Imatrix is calculated based on calibration data, and it helps determine the importance of different model activations during the quantization process. The idea is to preserve the most important information during quantization, which can help reduce the loss of model performance and lead to better performance, especially when the calibration data is diverse.
[2]
If you want any specific quantization to be added, feel free to ask.
This is an attempt to create a model that combines multiple "established" 7Bs and a very small WIP private dataset with
Eros' raw creative power. In terms of instruction formats, ChatML and Alpaca work best. The merge isn't purely ChatML, and as such, my previous attempts to integrate it with ChatML strings out of the box were Sisyphean and uninformed.
1 - sources:
2 - model: localfultonextractor/sumitest02
3 layer_range: [0, 32]
4 - model: tavtav/eros-7b-test
5 layer_range: [0, 32]
6merge_method: slerp
7base_model: localfultonextractor/sumitest02
8parameters:
9 t:
10 - filter: self_attn
11 value: [0, 0.2, 0.4, 0.55, 0.8]
12 - filter: mlp
13 value: [0.7, 0.3, 0.4, 0.3, 0]
14 - value: 0.37 # fallback for rest of tensors
15dtype: float16