mergekit merge arxiv:2311.03099 arxiv:2306.01708 base_model:jondurbin/bagel-dpo-8x7b-v0.2 base_model:mistralai/Mixtral-8x7B-v0.1 base_model:Sao10K/Sensualize-Mixtral-bf16 base_model:Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora base_model:mistralai/Mixtral-8x7B-Instruct-v0.1 region:us
---
base_model:
- jondurbin/bagel-dpo-8x7b-v0.2
- mistralai/Mixtral-8x7B-v0.1
- Sao10K/Sensualize-Mixtral-bf16
- mistralai/Mixtral-8x7B-v0.1
- Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora
- mistralai/Mixtral-8x7B-Instruct-v0.1
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
- `3.7b6h` -- 3.7bpw, 6bit lm_head
- `5b6h` -- 5bpw, 6bit lm_head
- `6b6h` -- 6bpw, 6bit lm_head


Requires ExllamaV2 version 0.0.12 and up.

Original model link: [ycros/BagelWorldTour-8x7B](https://huggingface.co/ycros/BagelWorldTour-8x7B)

Original model README below.

***
# BagelWorldTour

Requested by [kalomaze](https://huggingface.co/kalomaze)

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 [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) as a base.

### Models Merged

The following models were included in the merge:
* [jondurbin/bagel-dpo-8x7b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-8x7b-v0.2)
* [Sao10K/Sensualize-Mixtral-bf16](https://huggingface.co/Sao10K/Sensualize-Mixtral-bf16)
* [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) + [Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora](https://huggingface.co/Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora)
* [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: mistralai/Mixtral-8x7B-v0.1
models:
  - model: mistralai/Mixtral-8x7B-v0.1+Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora
    parameters:
      density: 0.5
      weight: 0.1
  - model: Sao10K/Sensualize-Mixtral-bf16
    parameters:
      density: 0.5
      weight: 0.1
  - model: mistralai/Mixtral-8x7B-Instruct-v0.1
    parameters:
      density: 0.66
      weight: 1.0
  - model: jondurbin/bagel-dpo-8x7b-v0.2
    parameters:
      density: 0.66
      weight: 0.5
merge_method: dare_ties
dtype: bfloat16

```

