---
base_model: []
tags:
- mergekit
- merge

---

Quantized using 200 samples of 8192 tokens from an RP-oriented [PIPPA](https://huggingface.co/datasets/royallab/PIPPA-cleaned) dataset.

Branches:
- `main` -- `measurement.json`
- `2.25b6h` -- 2.25bpw, 6bit lm_head
- `3.5b6h` -- 3.5bpw, 6bit lm_head
- `6b6h` -- 6bpw, 6bit lm_head


Requires ExllamaV2 version 0.0.12 and up.

Original model link: [rAIfle/0x01-7x8b-hf](https://huggingface.co/rAIfle/0x01-7x8b-hf)

Original model README below.

***
# 0x01-7x8B-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.

## 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

```