L3-OVA-Test-8B-GGUF / README.md
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---
base_model:
- Sao10K/L3-8B-Stheno-v3.2
- meta-llama/Meta-Llama-3-8B-Instruct
- ChaoticNeutrals/Domain-Fusion-L3-8B
- ChaoticNeutrals/Hathor_RP-v.01-L3-8B
- ChaoticNeutrals/Poppy_Porpoise-1.4-L3-8B
- ChaoticNeutrals/Templar_v1_8B
library_name: transformers
tags:
- mergekit
- merge
---
![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)
# QuantFactory/L3-OVA-Test-8B-GGUF
This is quantized version of [Casual-Autopsy/L3-OVA-Test-8B](https://huggingface.co/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](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/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](https://huggingface.co/Sao10K/L3-8B-Stheno-v3.2)
* [ChaoticNeutrals/Domain-Fusion-L3-8B](https://huggingface.co/ChaoticNeutrals/Domain-Fusion-L3-8B)
* [ChaoticNeutrals/Hathor_RP-v.01-L3-8B](https://huggingface.co/ChaoticNeutrals/Hathor_RP-v.01-L3-8B)
* [ChaoticNeutrals/Poppy_Porpoise-1.4-L3-8B](https://huggingface.co/ChaoticNeutrals/Poppy_Porpoise-1.4-L3-8B)
* [ChaoticNeutrals/Templar_v1_8B](https://huggingface.co/ChaoticNeutrals/Templar_v1_8B)
### 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
```