README.md

---
license: other
library_name: transformers
tags:
- mergekit
- merge
- mistral
- not-for-all-audiences
base_model:
- ABX-AI/Cerebral-Infinity-7B
- ABX-AI/Starfinite-Laymospice-v2-7B
model-index:
- name: Quantum-Citrus-9B
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 65.19
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Quantum-Citrus-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 84.75
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Quantum-Citrus-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.58
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Quantum-Citrus-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 55.96
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Quantum-Citrus-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 79.4
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Quantum-Citrus-9B
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 50.57
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Quantum-Citrus-9B
      name: Open LLM Leaderboard
---
# GGUF / IQ / Imatrix for [Quantum-Citrus-9B](https://huggingface.co/ABX-AI/Quantum-Citrus-9B)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65d936ad52eca001fdcd3245/J0snW3yfLadLuMYERL6X5.png)

**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.


# 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](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/Starfinite-Laymospice-v2-7B](https://huggingface.co/ABX-AI/Starfinite-Laymospice-v2-7B)
* [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/Starfinite-Laymospice-v2-7B
        layer_range: [12, 32]
merge_method: passthrough
dtype: float16
```

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ABX-AI__Quantum-Citrus-9B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |66.74|
|AI2 Reasoning Challenge (25-Shot)|65.19|
|HellaSwag (10-Shot)              |84.75|
|MMLU (5-Shot)                    |64.58|
|TruthfulQA (0-shot)              |55.96|
|Winogrande (5-shot)              |79.40|
|GSM8k (5-shot)                   |50.57|