ABX-AI/Cerebral-Lemonade-9B-GGUF-IQ-Imatrix

GGUF / IQ / Imatrix for 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] [2]

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.

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
• ABX-AI/Cerebral-Infinity-7B

Configuration

The following YAML configuration was used to produce this model:

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