Quantum-Citrus-9B-GGUF-IQ-Imatrix

GGUF / IQ / Imatrix for Quantum-Citrus-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.

Quantum-Citrus-9B

This merge is another attempt at making and intelligent, refined and unaligned model.

Based on my tests so far, it has accomplished the goals, and I am continuing to experiment with my interactions with it.

It includes previous merges of Starling, Cerebrum, LemonadeRP, InfinityRP, and deep down has a base of layla v0.1, as I am not that happy with the result form using v0.2.

The model is intended for fictional storytelling and roleplaying and may not be intended for all audences.

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/Starfinite-Laymospice-v2-7B
• 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/Starfinite-Laymospice-v2-7B
        layer_range: [12, 32]
merge_method: passthrough
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here