---
tags:
- iMat
- GGUF
- merge
---


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PROUDLY PRESENTS         
```
# 0x01-8x7b-iMat-GGUF

Quantized from fp16 with love.
* Quantizations made possible using .imatrix file from [this](https://huggingface.co/datasets/ikawrakow/imatrix-from-wiki-train) repo (special thanks to [ikawrakow](https://huggingface.co/ikawrakow) again)

For a brief rundown of iMatrix quant performance please see this [PR](https://github.com/ggerganov/llama.cpp/pull/5747)

<i>All quants are verified working prior to uploading to repo for your safety and convenience. </i>

Please note importance matrix quantizations are a work in progress, IQ3 and above is recommended for best results. 

<b>Tip:</b> Pick a size that can fit in your GPU while still allowing some room for context for best speed. You may need to pad this further depending on if you are running image gen or TTS as well.

Original model card can be found [here](https://huggingface.co/rAIfle/0x01-8x7b-hf) and below. Check there for optimal settings.


# 0x01-8x7B-hf

![grinning female android, cyberpunk, robotic, biomechanical, serial number "0x01"](https://files.catbox.moe/je2zar.png)

here we go again. multi-step merge, various models involved at various ratios with various methods. 

this thing came to me in a fever dream when I was hung over, but after slightly tweaking the recipe it turned out surprisingly decent. using with the settings included.

## Update: 
The following settings have proved to work good too:
- Context: https://files.catbox.moe/q91rca.json
- Instruct: https://files.catbox.moe/2w8ja2.json
- Textgen: https://files.catbox.moe/s25rad.json


## Constituent parts
```yaml
# primordial_slop_a:
  - model: mistralai/Mixtral-8x7B-v0.1+retrieval-bar/Mixtral-8x7B-v0.1_case-briefs
  - model: mistralai/Mixtral-8x7B-v0.1+SeanWu25/Mixtral_8x7b_Medicine
  - model: mistralai/Mixtral-8x7B-v0.1+SeanWu25/Mixtral_8x7b_WuKurtz
  - model: mistralai/Mixtral-8x7B-v0.1+Epiculous/crunchy-onion-lora
  - model: mistralai/Mixtral-8x7B-v0.1+maxkretchmer/gc-mixtral
# primordial_slop_b:
  - model: Envoid/Mixtral-Instruct-ITR-8x7B
  - model: crestf411/daybreak-mixtral-8x7b-v1.0-hf
  - model: NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO
  - model: orangetin/OpenHermes-Mixtral-8x7B
  - model: mistralai/Mixtral-8x7B-Instruct-v0.1+idegroup/PhyAssistant
  - model: ycros/crunchy-onion-nx
  - model: jondurbin/bagel-dpo-8x7b-v0.2
  - model: amoldwalunj/Mixtral-8x7B-Instruct-v0.1-legal_finetune_mixtral_32k
# primordial_slop_c: a+b
# primordial_slop_d:
  - model: Sao10K/Sensualize-Mixtral-bf16
  - model: Envoid/Mixtral-Instruct-ITR-DADA-8x7B
```

# mergekit

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the SLERP merge method.

### Models Merged

The following models were included in the merge:
* ./primordial_slop_d
* ./primordial_slop_c

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: ./primordial_slop_c
  - model: ./primordial_slop_d
merge_method: slerp
base_model: ./primordial_slop_c
parameters:
  t:
    - value: 0.33
dtype: float16

```