"NOTES: This model seems to be overtly confident leading to hallucinations, normalization has seemed to also break the long context chaining. I do not recommend this model." Use the previous, Kunoccini-7B-128k-test, in this collection.
It stands for Importance Matrix, a technique used to improve the quality of quantized models.
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.
One of the benefits of using an Imatrix is that it can lead to better model performance, especially when the calibration data is diverse.
