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---
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
```
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