---
library_name: transformers
license: mit
---
# Phi-4 SLERP Merge Model

## Model Description  
This is a merged language model created using the **Spherical Linear Interpolation (SLERP) merge method**, allowing for a smooth blend of features from both parent models across different layers. The merge optimizes reasoning, general knowledge, and task-specific performance by strategically interpolating attention and MLP components.

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## Merge Details  

**Merge Method:**  
The model was merged using **SLERP (Spherical Linear Interpolation)** rather than a traditional linear merge, ensuring a well-balanced combination of both source models while maintaining coherent weight transitions.

**Base Model:**  
- **bunnycore/Phi-4-RR-Shoup** (used as the primary base)

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## Models Merged  
The following models were included in this merge:

1. **bunnycore/Phi-4-RR-Shoup** (Primary base)  
2. **bunnycore/Phi-4-Model-Stock-v4**  

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## Configuration  
The following YAML configuration was used to produce this merged model:

```yaml
slices:
- sources:
  - model: bunnycore/Phi-4-RR-Shoup
    layer_range:
    - 0
    - 32
  - model: bunnycore/Phi-4-Model-Stock-v4
    layer_range:
    - 0
    - 32
merge_method: slerp
base_model: bunnycore/Phi-4-RR-Shoup
parameters:
  t:
  - filter: self_attn
    value:
    - 0
    - 0.5
    - 0.3
    - 0.7
    - 1
  - filter: mlp
    value:
    - 1
    - 0.5
    - 0.7
    - 0.3
    - 0
  - value: 0.5
dtype: bfloat16