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---
base_model:
- ABX-AI/Infinite-Laymons-7B
- ABX-AI/Cerebral-Infinity-7B
library_name: transformers
tags:
- mergekit
- merge
- mistral
- not-for-all-audiences
---
# GGUF / IQ / Imatrix for [Cerebral-Lemonade-9B](https://huggingface.co/ABX-AI/Cerebral-Lemonade-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 custom kink.
# Cerebral-Lemonade-9B
The concept behind this merge was to use the improved reasoning of of Cerebral-Infinity-7B, and merge it with the improved originality of Infinite-Laymons-7B.
I think the experiment worked, and so far I am happy with the results.
This model is intended for fictional storytelling and role-playing, with a focus on more original conversations and less alignment.
## Merge Details
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
### Merge Method
This model was merged using the passthrough merge method.
### Models Merged
The following models were included in the merge:
* [ABX-AI/Infinite-Laymons-7B](https://huggingface.co/ABX-AI/Infinite-Laymons-7B)
* [ABX-AI/Cerebral-Infinity-7B](https://huggingface.co/ABX-AI/Cerebral-Infinity-7B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: ABX-AI/Cerebral-Infinity-7B
layer_range: [0, 20]
- sources:
- model: ABX-AI/Infinite-Laymons-7B
layer_range: [12, 32]
merge_method: passthrough
dtype: float16
``` |