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---
base_model: []
library_name: transformers
tags:
- mergekit
- merge
- llama
- not-for-all-audiences
---
# GGUF / IQ / Imatrix for [Silver-Sun-v2-11B](https://huggingface.co/ABX-AI/Silver-Sun-v2-11B)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65d936ad52eca001fdcd3245/9DobeVeyL98G7QUufEeQg.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.

# Silver-Sun-v2-11B

> This is an updated version of Silver-Sun-11B. The change is that now the Solstice-FKL-v2-10.7B merge uses Sao10K/Fimbulvetr-11B-v2 instead of v1.
> Additionally, the config of the original Silver-Sun was wrong, and I have also updated that.
> As expected, this is a HIGHLY uncensored model. It should perform even better than the v1 due to the updated Fimb, and the fixed config.

**Works with Alpaca, and from my tests, also ChatML. However Alpaca may be a better option. Try it out and use whatever works better for you.**
**Due to a quirk with Solar, if you want the best quality either launch at 4K context, or launch at 8K (and possibly beyond - have not tested it that high) with 4k context pre-loaded in the prompt.**

> This model is intended for fictional storytelling and writing, focusing on NSFW capabilities and lack of censorship for RP reasons.

## 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 SLERP merge method.

### Models Merged

The following models were included in the merge:
* [Himitsui/Kaiju-11B](https://huggingface.co/Himitsui/Kaiju-11B)
* ABX-AI/Solstice-FKL-v2-10.7B
>[!NOTE]
>A mixture of [Sao10K/Solstice-11B-v1](https://huggingface.co/Sao10K/Solstice-11B-v1) and
>[ABX-AI/Fimbulvetr-Kuro-Lotus-v2-10.7B] which is updated saishf/Fimbulvetr-Kuro-Lotus-10.7B with Fimb v2

### OpenLLM Eval Results

[Detailed Results + Failed GSM8K](https://huggingface.co/datasets/open-llm-leaderboard/details_ABX-AI__Silver-Sun-v2-11B)


>[!NOTE]
>I had to remove GSM8K from the results and manually re-average the rest. GSM8K failed due to some issue with formatting, which is not something I experienced during practical usage.
>By removing the GSM8K score, the average is VERY close to upstage/SOLAR-10.7B-v1.0 (74.20), which would make sense.
>Feel free to ignore the actual average and use the other scores individually for reference.

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |74.04|
|AI2 Reasoning Challenge (25-Shot)|69.88|
|HellaSwag (10-Shot)              |87.81|
|MMLU (5-Shot)                    |66.74|
|TruthfulQA (0-shot)              |62.49|
|Winogrande (5-shot)              |83.27|

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
      - model: ./MODELS/Solstice-FKL-v2-10.7B
        layer_range: [0, 48]
      - model: Himitsui/Kaiju-11B
        layer_range: [0, 48]
merge_method: slerp
base_model: ./MODELS/Solstice-FKL-v2-10.7B
parameters:
  t:
    - filter: self_attn
      value: [0.6, 0.7, 0.8, 0.9, 1]
    - filter: mlp
      value: [0.4, 0.3, 0.2, 0.1, 0]
    - value: 0.5
dtype: bfloat16
```