maid-yuzu-v4

This is a merge of pre-trained language models created using mergekit.

This model is a model that I merged with several models I know because I had leftover credits for merging. Of course, the results are not good. Please do not use it.

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using mistralai/Mixtral-8x7B-v0.1 as a base.

Models Merged

The following models were included in the merge:

• cognitivecomputations/dolphin-2.7-mixtral-8x7b
• Sao10K/Sensualize-Mixtral-bf16
• jondurbin/bagel-dpo-8x7b-v0.2
• mistralai/Mixtral-8x7B-v0.1 + Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora
• smelborp/MixtralOrochi8x7B

Configuration

The following YAML configuration was used to produce this model:

base_model:
  model:
    path: mistralai/Mixtral-8x7B-v0.1
dtype: bfloat16
merge_method: dare_ties
slices:
- sources:
  - layer_range: [0, 32]
    model:
      model:
        path: smelborp/MixtralOrochi8x7B
    parameters:
      density: 0.75
      weight: 0.7
  - layer_range: [0, 32]
    model:
      model:
        path: cognitivecomputations/dolphin-2.7-mixtral-8x7b
    parameters:
      density: 0.6
      weight: 0.1
  - layer_range: [0, 32]
    model:
      model:
        path: jondurbin/bagel-dpo-8x7b-v0.2
    parameters:
      density: 0.6
      weight: 0.1
  - layer_range: [0, 32]
    model:
      lora:
        path: Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora
      model:
        path: mistralai/Mixtral-8x7B-v0.1
    parameters:
      density: 0.5
      weight: 0.25
  - layer_range: [0, 32]
    model:
      model:
        path: Sao10K/Sensualize-Mixtral-bf16
    parameters:
      density: 0.5
      weight: 0.2
  - layer_range: [0, 32]
    model:
      model:
        path: mistralai/Mixtral-8x7B-v0.1