---
base_model:
- LeroyDyer/_Spydaz_Web_AI_AGI_R1_Student_Coder
- LeroyDyer/_Spydaz_Web_AI_AGI_R1_X1
- LeroyDyer/_Spydaz_Web_AI_AGI_R1_Teacher_Coder
library_name: transformers
tags:
- mergekit
- merge

---
# merge  --- - -Beware Reward training can make mistakes in the tesor stack ! Which pytorch does not like !  So A RE-MERGE with base will repair it !

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).


This merge took it to the top of my models list! But my musr/Ipevel went down ?


## Merge Details
### Merge Method

This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [LeroyDyer/_Spydaz_Web_AI_AGI_R1_X1](https://huggingface.co/LeroyDyer/_Spydaz_Web_AI_AGI_R1_X1) as a base.

### Models Merged

The following models were included in the merge:
* [LeroyDyer/_Spydaz_Web_AI_AGI_R1_Student_Coder](https://huggingface.co/LeroyDyer/_Spydaz_Web_AI_AGI_R1_Student_Coder)
* [LeroyDyer/_Spydaz_Web_AI_AGI_R1_Teacher_Coder](https://huggingface.co/LeroyDyer/_Spydaz_Web_AI_AGI_R1_Teacher_Coder)

### Configuration

The following YAML configuration was used to produce this model:

```yaml

models:
  - model: LeroyDyer/_Spydaz_Web_AI_AGI_R1_Student_Coder
    parameters:
      density: 0.256
      weight: [0.256, 0.128, 0.256, 0.128] # weight gradient
  - model: LeroyDyer/_Spydaz_Web_AI_AGI_R1_Teacher_Coder
    parameters:
      density: 0.256
      weight: [0.128, 0.256, 0.128, 0.256] # weight gradient
  - model: LeroyDyer/_Spydaz_Web_AI_AGI_R1_X1
    parameters:
      density: 0.768
      weight:
        - filter: mlp
          value: 0.768
        - value: 0.512
merge_method: ties
base_model: LeroyDyer/_Spydaz_Web_AI_AGI_R1_X1
parameters:
  normalize: true
  int8_mask: true
dtype: float16

```