QuantFactory/L3-OVA-Test-8B-GGUF
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:
- Sao10K/L3-8B-Stheno-v3.2
- ChaoticNeutrals/Domain-Fusion-L3-8B
- ChaoticNeutrals/Hathor_RP-v.01-L3-8B
- ChaoticNeutrals/Poppy_Porpoise-1.4-L3-8B
- ChaoticNeutrals/Templar_v1_8B
Configuration
The following YAML configuration was used to produce this model:
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
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