Custom Model "Dolphin2Star1" Merged by Noodlz. 12.5B linear merged from the uncensored mistral 7B v0.2 as the base, with the fine tunes of StarlingLM 7B Beta that's originally mistral 7B v0.1

have fun =)

license: apache-2.0

base_model:

cognitivecomputations/dolphin-2.8-mistral-7b-v02
NexusFlow/Starling-LM-7B-beta library_name: transformers tags:
mergekit
merge

output_folder

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

Merge Details

Merge Method

This model was merged using the linear merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

merge_method: linear
parameters:
  weight: 1.0
slices:
  - sources:
      - model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
        layer_range: [0,1]
      - model: NexusFlow/Starling-LM-7B-beta
        layer_range: [0,1]
        parameters: 
          weight: 0
  - sources:
      - model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
        layer_range: [1,8]        
  - sources:
      - model: NexusFlow/Starling-LM-7B-beta
        layer_range: [4,12]
  - sources:
      - model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
        layer_range: [8,16]        
  - sources:
      - model: NexusFlow/Starling-LM-7B-beta
        layer_range: [12,20]  
  - sources:
      - model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
        layer_range: [16,24]        
  - sources:
      - model: NexusFlow/Starling-LM-7B-beta
        layer_range: [20,28]
  - sources:
      - model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
        layer_range: [24,31]        
  - sources:
      - model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
        layer_range: [31,32]
      - model: NexusFlow/Starling-LM-7B-beta
        layer_range: [31,32]
        parameters: 
          weight: 0          
dtype: float16
tokenizer_source: model:cognitivecomputations/dolphin-2.8-mistral-7b-v02