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 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:
Merge Details
Merge Method
This model was merged using the Passthrough merge method using bunnycore/Phi-4-Model-Stock-v4 + 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:
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
Detailed results can be found here
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 |
- Downloads last month
- 59
Model tree for bunnycore/Phi-4-ReasoningRP
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard67.360
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard55.880
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard44.340
- acc_norm on GPQA (0-shot)Open LLM Leaderboard12.530
- acc_norm on MuSR (0-shot)Open LLM Leaderboard15.140
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard49.120