RichardErkhov/Nisk36_-_MergeModelAll-gguf

Quantization made by Richard Erkhov.

Github

Discord

Request more models

MergeModelAll - GGUF

• Model creator: https://huggingface.co/Nisk36/
• Original model: https://huggingface.co/Nisk36/MergeModelAll/

Name	Quant method	Size
MergeModelAll.Q2_K.gguf	Q2_K	2.36GB
MergeModelAll.IQ3_XS.gguf	IQ3_XS	2.6GB
MergeModelAll.IQ3_S.gguf	IQ3_S	2.75GB
MergeModelAll.Q3_K_S.gguf	Q3_K_S	2.75GB
MergeModelAll.IQ3_M.gguf	IQ3_M	2.9GB
MergeModelAll.Q3_K.gguf	Q3_K	3.07GB
MergeModelAll.Q3_K_M.gguf	Q3_K_M	3.07GB
MergeModelAll.Q3_K_L.gguf	Q3_K_L	3.35GB
MergeModelAll.IQ4_XS.gguf	IQ4_XS	3.4GB
MergeModelAll.Q4_0.gguf	Q4_0	3.56GB
MergeModelAll.IQ4_NL.gguf	IQ4_NL	3.58GB
MergeModelAll.Q4_K_S.gguf	Q4_K_S	3.59GB
MergeModelAll.Q4_K.gguf	Q4_K	3.8GB
MergeModelAll.Q4_K_M.gguf	Q4_K_M	3.8GB
MergeModelAll.Q4_1.gguf	Q4_1	3.95GB
MergeModelAll.Q5_0.gguf	Q5_0	4.33GB
MergeModelAll.Q5_K_S.gguf	Q5_K_S	4.33GB
MergeModelAll.Q5_K.gguf	Q5_K	4.45GB
MergeModelAll.Q5_K_M.gguf	Q5_K_M	4.45GB
MergeModelAll.Q5_1.gguf	Q5_1	4.72GB
MergeModelAll.Q6_K.gguf	Q6_K	5.15GB
MergeModelAll.Q8_0.gguf	Q8_0	6.67GB

Original model description:

base_model:

• Nisk36/finetuned-lmsys_vicuna-7b-v1.5
• Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct library_name: transformers tags:
• mergekit
• merge

---

final_model

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:

• Nisk36/finetuned-lmsys_vicuna-7b-v1.5
• Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct

Configuration

The following YAML configuration was used to produce this model:

dtype: bfloat16
merge_method: linear
parameters:
  int8_mask: 1.0
  normalize: 1.0
slices:
- sources:
  - layer_range: [0, 4]
    model: Nisk36/finetuned-lmsys_vicuna-7b-v1.5
    parameters:
      weight: 0.6235769265047518
  - layer_range: [0, 4]
    model: Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct
    parameters:
      weight: 0.7274442555681364
- sources:
  - layer_range: [4, 8]
    model: Nisk36/finetuned-lmsys_vicuna-7b-v1.5
    parameters:
      weight: 0.5271398694239577
  - layer_range: [4, 8]
    model: Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct
    parameters:
      weight: 0.3489250438855029
- sources:
  - layer_range: [8, 12]
    model: Nisk36/finetuned-lmsys_vicuna-7b-v1.5
    parameters:
      weight: 0.15496421762028023
  - layer_range: [8, 12]
    model: Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct
    parameters:
      weight: 0.541330668871115
- sources:
  - layer_range: [12, 16]
    model: Nisk36/finetuned-lmsys_vicuna-7b-v1.5
    parameters:
      weight: 0.5267269624685371
  - layer_range: [12, 16]
    model: Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct
    parameters:
      weight: 0.8265113027826562
- sources:
  - layer_range: [16, 20]
    model: Nisk36/finetuned-lmsys_vicuna-7b-v1.5
    parameters:
      weight: 0.6599861585345389
  - layer_range: [16, 20]
    model: Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct
    parameters:
      weight: -0.249060520039947
- sources:
  - layer_range: [20, 24]
    model: Nisk36/finetuned-lmsys_vicuna-7b-v1.5
    parameters:
      weight: 0.7761318532349375
  - layer_range: [20, 24]
    model: Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct
    parameters:
      weight: 0.7040995904551324
- sources:
  - layer_range: [24, 28]
    model: Nisk36/finetuned-lmsys_vicuna-7b-v1.5
    parameters:
      weight: 0.40152017541360374
  - layer_range: [24, 28]
    model: Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct
    parameters:
      weight: 0.767141768059921
- sources:
  - layer_range: [28, 32]
    model: Nisk36/finetuned-lmsys_vicuna-7b-v1.5
    parameters:
      weight: -0.004536646708608122
  - layer_range: [28, 32]
    model: Nisk36/FT_elyza_ELYZA-japanese-Llama-2-7b-instruct
    parameters:
      weight: 0.8295357241419378