---
base_model: []
library_name: transformers
tags:
- mergekit
- merge
- not-for-all-audiences
---

![](eemaid.png)

# Eclectic-Maid-7B-v2

This model is much better over original model, I believe.  The recipes are not exact below but at least you get an idea of what models are involved.
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details

See Below

### Merge Method

This model was merged using the passthrough merge method.

### Models Merged

See Below

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
    - model: "Maid-Reborn-v22-10B"
      layer_range: [0, 16]
  - sources:
    - model: "Maid-Reborn-v22-10B"
      layer_range: [8, 24]
  - sources:
    - model: "Maid-Reborn-v22-10B"
      layer_range: [17, 32]
merge_method: passthrough
dtype: float16

```
```yaml
models:
  - model: mistralai/Mistral-7B-v0.1
    # No parameters necessary for base model
  - model: cognitivecomputations/WestLake-7B-v2-laser
    parameters:
      density: 0.58
      weight:  [0.3877, 0.1636, 0.186, 0.0502]
  - model: senseable/garten2-7b
    parameters:
      density: 0.58
      weight:  [0.234, 0.2423, 0.2148, 0.2775]
  - model: berkeley-nest/Starling-LM-7B-alpha
    parameters:
      density: 0.58
      weight:  [0.1593, 0.1573, 0.1693, 0.3413]
  - model: mlabonne/AlphaMonarch-7B
    parameters:
      density: 0.58
      weight:  [0.219, 0.4368, 0.4299, 0.331]
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16
name: Maid-Reborn-v22
```
```yaml
models: 
  - model: mistralai/Mistral-7B-Instruct-v0.2
    # no parameters necessary for base model
  - model: xDAN-AI/xDAN-L1-Chat-RL-v1
    parameters:
      weight: 0.4
      density: 0.8
  - model: Undi95/BigL-7B
    parameters:
      weight: 0.3
      density: 0.8
  - model: SanjiWatsuki/Loyal-Toppy-Bruins-Maid-7B-DARE
    parameters:
      weight: 0.2
      density: 0.4
  - model: NeverSleep/Noromaid-7B-0.4-DPO
    parameters:
      weight: 0.2
      density: 0.4
  - model: NSFW_DPO_Noromaid-7B-v2
    parameters:
      weight: 0.2
      density: 0.4
merge_method: dare_ties
base_model: mistralai/Mistral-7B-Instruct-v0.2
parameters:
  int8_mask: true
dtype: bfloat16
```