---

base_model:
- defog/llama-3-sqlcoder-8b
- meta-llama/Meta-Llama-3-8B-Instruct
library_name: transformers
tags:
- mergekit
- merge


---

![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)

# QuantFactory/sepctrum-ties-sqlcoder-8b-GGUF
This is quantized version of [arcee-ai/sepctrum-ties-sqlcoder-8b](https://huggingface.co/arcee-ai/sepctrum-ties-sqlcoder-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:
* [defog/llama-3-sqlcoder-8b](https://huggingface.co/defog/llama-3-sqlcoder-8b)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
merge_method: ties
base_model: meta-llama/Meta-Llama-3-8B-Instruct
models:
- model: defog/llama-3-sqlcoder-8b
  parameters:
    weight:
    - filter: mlp.down_proj
      value: [0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0.5, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0]
    - filter: mlp.gate_proj
      value: [0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5]
    - filter: mlp.up_proj
      value: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0, 0, 0, 0, 0.5, 0, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
    - filter: self_attn.k_proj
      value: [0.5, 0.5, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0]
    - filter: self_attn.o_proj
      value: [0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0.5, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0]
    - filter: self_attn.q_proj
      value: [0, 0, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5]
    - filter: self_attn.v_proj
      value: [0.5, 0, 0.5, 0, 0, 0.5, 0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0, 0, 0, 0, 0.5, 0.5, 0, 0, 0, 0, 0.5, 0, 0, 0.5, 0, 0, 0.5, 0.5]
    - value: [0]  
    density: 0.75
- model: meta-llama/Meta-Llama-3-8B-Instruct
  parameters:
    weight:
    - filter: mlp.down_proj
      value: [1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1]
    - filter: mlp.gate_proj
      value: [1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 0.5]
    - filter: mlp.up_proj
      value: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 1, 1, 1, 1, 0.5, 1, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
    - filter: self_attn.k_proj
      value: [0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 1]
    - filter: self_attn.o_proj
      value: [0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1]
    - filter: self_attn.q_proj
      value: [1, 1, 0.5, 0.5, 0.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5]
    - filter: self_attn.v_proj
      value: [0.5, 1, 0.5, 1, 1, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 1, 1, 1, 0.5, 0.5, 1, 1, 1, 1, 0.5, 1, 1, 0.5, 1, 1, 0.5, 0.5]
    - value: [1] 
    density: 1.0
parameters: {normalize: true, int8_mask: true}
dtype: bfloat16

```