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---
base_model:
- localfultonextractor/Erosumika-7B-v2
- Endevor/InfinityRP-v1-7B
library_name: transformers
tags:
- mergekit
- merge
- mistral
- not-for-all-audiences
---
GGUF / IQ / Imatrix for [Infinite-Sumika-9B](https://huggingface.co/ABX-AI/Infinite-Sumika-9B)
**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]](https://github.com/ggerganov/llama.cpp/discussions/5006) [[2]](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384)
The imatrix.txt file that I used contains general, semi-random data, with some added extra kink.
# Infinite-Sumika-9B
This model is intended for fictional role-playing and storywriting.
It seems to be doing good with longer text, and prefers to write longer, storytelling-like responses sometimes.
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the passthrough merge method.
### Models Merged
The following models were included in the merge:
* [localfultonextractor/Erosumika-7B-v2](https://huggingface.co/localfultonextractor/Erosumika-7B-v2)
* [Endevor/InfinityRP-v1-7B](https://huggingface.co/Endevor/InfinityRP-v1-7B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: Endevor/InfinityRP-v1-7B
layer_range: [0, 20]
- sources:
- model: localfultonextractor/Erosumika-7B-v2
layer_range: [12, 32]
merge_method: passthrough
dtype: float16
``` |