melino2000/tiny-llama-merge-evo

final_merge

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

Merge Details

Merge Method

This model was merged using the task arithmetic merge method using /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064 as a base.

Models Merged

The following models were included in the merge:

• /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950

Configuration

The following YAML configuration was used to produce this model:

base_model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
dtype: bfloat16
merge_method: task_arithmetic
parameters:
  int8_mask: 1.0
  normalize: 0.0
slices:
- sources:
  - layer_range: [0, 2]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 0.903670769683462
  - layer_range: [0, 2]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [2, 4]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 0.8677123591929141
  - layer_range: [2, 4]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [4, 6]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.0080967885131624
  - layer_range: [4, 6]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [6, 8]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.288794492088366
  - layer_range: [6, 8]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [8, 10]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.0927250789898328
  - layer_range: [8, 10]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [10, 12]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.002818025226096
  - layer_range: [10, 12]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [12, 14]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.0346267702747531
  - layer_range: [12, 14]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [14, 16]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.060865068400883
  - layer_range: [14, 16]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [16, 18]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.0141257624580193
  - layer_range: [16, 18]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [18, 20]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.2727977176081706
  - layer_range: [18, 20]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064
- sources:
  - layer_range: [20, 22]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_chinese_1905817950
    parameters:
      weight: 1.2137521068579595
  - layer_range: [20, 22]
    model: /kaggle/working/evol_merge_storage/input_models/TinyLlama_v1.1_684560064