QuantFactory/L3-OVA-Test-8B-GGUF

Name: L3-OVA-Test-8B-GGUF
Availability: InStock

This is quantized version of Casual-Autopsy/L3-OVA-Test-8B created using llama.cpp

Original Model Card

merge

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

Merge Details

Merge Method

This model was merged using the TIES merge method using meta-llama/Meta-Llama-3-8B-Instruct as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

yaml

models:
  - model: meta-llama/Meta-Llama-3-8B-Instruct
  - model: meta-llama/Meta-Llama-3-8B-Instruct
    parameters:
      density: 0.5
      weight: 0.5
  - model: ChaoticNeutrals/Templar_v1_8B
    parameters:
      density: 0.75
      weight: [0.25, 0.0625, 0.0625, 0.0625, 0.0625]
  - model: ChaoticNeutrals/Hathor_RP-v.01-L3-8B
    parameters:
      density: 0.75
      weight: [0.0625, 0.25, 0.0625, 0.0625, 0.0625]
  - model: Sao10K/L3-8B-Stheno-v3.2
    parameters:
      density: 0.75
      weight: [0.0625, 0.0625, 0.25, 0.0625, 0.0625]
  - model: ChaoticNeutrals/Poppy_Porpoise-1.4-L3-8B
    parameters:
      density: 0.75
      weight: [0.0625, 0.0625, 0.0625, 0.25, 0.0625]
  - model: ChaoticNeutrals/Domain-Fusion-L3-8B
    parameters:
      density: 0.75
      weight: [0.0625, 0.0625, 0.0625, 0.0625, 0.25]
  - model: ChaoticNeutrals/Templar_v1_8B
    parameters:
      density: 0.25
      weight: [-0.125, -0.125, -0.125, -0.125, -0.5]
  - model: ChaoticNeutrals/Hathor_RP-v.01-L3-8B
    parameters:
      density: 0.25
      weight: [-0.125, -0.125, -0.5, -0.125, -0.125]
  - model: Sao10K/L3-8B-Stheno-v3.2
    parameters:
      density: 0.25
      weight: [-0.125, -0.5, -0.125, -0.125, -0.125]
  - model: ChaoticNeutrals/Poppy_Porpoise-1.4-L3-8B
    parameters:
      density: 0.25
      weight: [-0.125, -0.125, -0.125, -0.5, -0.125]
  - model: ChaoticNeutrals/Domain-Fusion-L3-8B
    parameters:
      density: 0.25
      weight: [-0.5, -0.125, -0.125, -0.125, -0.125]
merge_method: ties
base_model: meta-llama/Meta-Llama-3-8B-Instruct
parameters:
  normalize: false
  int8_mask: true
dtype: bfloat16