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Legion-V1A-LLaMa-70B-4.0bpw-h8-exl2

Text Generation
Transformers
Safetensors
llama
mergekit
Merge
conversational
text-generation-inference
4-bit precision
exl2
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Legion-V1A-LLaMa-70B-4.0bpw-h8-exl2
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---
base_model_relation: quantized
base_model:
- TareksTesting/Legion-V1A-LLaMa-70B
library_name: transformers
tags:
- mergekit
- merge
---
# 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 [DARE TIES](https://arxiv.org/abs/2311.03099) merge method using [TareksLab/M-BASE-SCE](https://huggingface.co/TareksLab/M-BASE-SCE) as a base.

### Models Merged

The following models were included in the merge:
* [TareksLab/M-MERGE1](https://huggingface.co/TareksLab/M-MERGE1)
* [TareksLab/M-MERGE3](https://huggingface.co/TareksLab/M-MERGE3)
* [TareksLab/M-MERGE2](https://huggingface.co/TareksLab/M-MERGE2)
* [TareksLab/M-MERGE4](https://huggingface.co/TareksLab/M-MERGE4)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: TareksLab/M-MERGE4
    parameters:
      weight: 
      - filter: self_attn
        value: [0.3, 0.1, 0.2]
      - filter: mlp
        value: [0.4, 0.2, 0.1]
      - value: 0.2
      density: 0.7
      lambda: 1.05
  - model: TareksLab/M-MERGE3
    parameters:
      weight: 
      - filter: self_attn
        value: [0.2, 0.1, 0.3]
      - filter: mlp
        value: [0.3, 0.1, 0.2]
      - value: 0.2
      density: 0.65
      lambda: 1.05
  - model: TareksLab/M-MERGE2
    parameters:
      weight: 
      - filter: self_attn
        value: [0.1, 0.3, 0.1]
      - filter: mlp
        value: [0.2, 0.3, 0.1]
      - value: 0.2
      density: 0.6
      lambda: 1.05
  - model: TareksLab/M-MERGE1
    parameters:
      weight: 
      - filter: self_attn
        value: [0.2, 0.2, 0.1]
      - filter: mlp
        value: [0.1, 0.2, 0.2]
      - value: 0.2
      density: 0.6
      lambda: 1
  - model: TareksLab/M-BASE-SCE
    parameters:
      weight: 
      - filter: self_attn
        value: [0.1, 0.3, 0.3]
      - filter: mlp
        value: [0.1, 0.2, 0.4]
      - value: 0.2
      density: 0.55
      lambda: 1
base_model: TareksLab/M-BASE-SCE
merge_method: dare_ties
parameters:
  normalize: false
  pad_to_multiple_of: 4
tokenizer:
  source: TareksLab/M-TOKENIZER-SCE
chat_template: llama3
dtype: bfloat16
```