GGUF / IQ / Imatrix for ABX-AI/Kuno-Lemon-7B
Requested by @ Nitral-AI.
Quants coming soon.
Why Importance Matrix?
Importance Matrix, at least based on my testing, has shown to improve the output and performance of "IQ"-type quantizations, where the compression becomes quite heavy. The Imatrix performs a calibration, using a provided dataset. Testing has shown that semi-randomized data can help perserve more important segments as the compression is applied.
Related discussions in Github: [1] [2]
The imatrix.txt file that I used contains general, semi-random data, with some added extra kink.
Kuno-Lemon-7B
This model is intended for role-playing and storywriting purposes.
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: SanjiWatsuki/Kunoichi-DPO-v2-7B
layer_range: [0, 32]
- model: KatyTheCutie/LemonadeRP-4.5.3
layer_range: [0, 32]
merge_method: slerp
base_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
parameters:
t:
- filter: self_attn
value: [0.75, 0.75, 0.75, 0.75, 0.75]
- filter: mlp
value: [0.25, 0.25, 0.25, 0.25, 0.25]
- value: 0.5
dtype: bfloat16
- Downloads last month
- 29