---
license: mit
library_name: transformers
tags:
- mergekit
- merge
base_model:
- bunnycore/Phi-4-Model-Stock-v4
- bunnycore/Phi-4-14B-1M-RRP-v1-lora
model-index:
- name: Phi-4-ReasoningRP
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 67.36
      name: strict accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Phi-4-ReasoningRP
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 55.88
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Phi-4-ReasoningRP
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 44.34
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Phi-4-ReasoningRP
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 12.53
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Phi-4-ReasoningRP
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 15.14
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Phi-4-ReasoningRP
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 49.12
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Phi-4-ReasoningRP
      name: Open LLM Leaderboard
---
This model is Phi-4 with a reasoning fine-tuned LoRA applied.  While it can follow a reasoning format, it's important to understand that its "thinking" isn't the same as more advanced reasoning models (like R1 or O1).  Think of it as Phi-4 with a helpful reasoning boost.

## What can it do?

This model is designed for roleplay and other reasoning-related tasks.  It's not intended to be a replacement for specialized reasoning models; it has its own strengths and limitations.

To activate the reasoning format, use the <think> tag within the system prompt.  This will encourage the model to structure its response in a step-by-step or explanatory manner.

### Chat Template:

```
<|im_start|>system<|im_sep|>{system_prompt}<|im_end|>
<|im_start|>user<|im_sep|>{user}<|im_end|>
<|im_start|>assistant<|im_sep|>
```
### Example System Prompt (with reasoning):


You are a helpful assistant. ```<think>``` Let's break this down step by step. First, we need to consider... Then, we can look at... Finally, we arrive at the answer. ```</think>```
Strengths:

- Capable of roleplay.
- Can follow a reasoning format when prompted.
- Based on the Phi-4 architecture.

### Benchmark:

![image/png](https://cdn-uploads.huggingface.co/production/uploads/63284f86cbc744f197050300/U9TcKlvryI9Xx_5uaUL4m.png)


## Merge Details
### Merge Method

This model was merged using the Passthrough merge method using [bunnycore/Phi-4-Model-Stock-v4](https://huggingface.co./bunnycore/Phi-4-Model-Stock-v4) + [bunnycore/Phi-4-14B-1M-RRP-v1-lora](https://huggingface.co./bunnycore/Phi-4-14B-1M-RRP-v1-lora) as a base.

### Models Merged

The following models were included in the merge:


### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: bunnycore/Phi-4-Model-Stock-v4+bunnycore/Phi-4-14B-1M-RRP-v1-lora
dtype: bfloat16
merge_method: passthrough
models:
  - model: bunnycore/Phi-4-Model-Stock-v4+bunnycore/Phi-4-14B-1M-RRP-v1-lora

```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/bunnycore__Phi-4-ReasoningRP-details)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |40.73|
|IFEval (0-Shot)    |67.36|
|BBH (3-Shot)       |55.88|
|MATH Lvl 5 (4-Shot)|44.34|
|GPQA (0-shot)      |12.53|
|MuSR (0-shot)      |15.14|
|MMLU-PRO (5-shot)  |49.12|