---
base_model:
- benhaotang/Phi-4-llama-t1-full
- prithivMLmods/Phi-4-QwQ
- win10/Phi-4-llama-t1-lora
library_name: transformers
tags:
- mergekit
- merge
datasets:
- NovaSky-AI/Sky-T1_data_17k
license: mit
model-index:
- name: phi4-qwq-sky-t1
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: wis-k/instruction-following-eval
      split: train
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 4.6
      name: averaged accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=benhaotang%2Fphi4-qwq-sky-t1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: SaylorTwift/bbh
      split: test
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 52.61
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=benhaotang%2Fphi4-qwq-sky-t1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: lighteval/MATH-Hard
      split: test
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 39.58
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=benhaotang%2Fphi4-qwq-sky-t1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      split: train
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 19.35
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=benhaotang%2Fphi4-qwq-sky-t1
      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: 21.38
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=benhaotang%2Fphi4-qwq-sky-t1
      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: 47.16
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=benhaotang%2Fphi4-qwq-sky-t1
      name: Open LLM Leaderboard
---
# merge

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

## Merge Details
### Merge Method

This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [prithivMLmods/Phi-4-QwQ](https://huggingface.co./prithivMLmods/Phi-4-QwQ) as a base.

### Models Merged

The following models were included in the merge:
* [benhaotang/Phi-4-llama-t1-full](https://huggingface.co./benhaotang/Phi-4-llama-t1-full) but actually [win10/Phi-4-llama-t1-lora](https://huggingface.co./win10/Phi-4-llama-t1-lora), this is who and where you should really thank.
* [prithivMLmods/Phi-4-QwQ](https://huggingface.co./prithivMLmods/Phi-4-QwQ)

### Running

- With Ollama

```
ollama run hf.co/benhaotang/phi4-qwq-sky-t1-Q4_K_M-GGUF
```

I suggest adding `SYSTEM "You are a helpful AI asistent. You always think step by step."` to triger step by step reasoning.

- With pytorch

```
import transformers
tokenizer = AutoTokenizer.from_pretrained("mircosoft/phi-4")
pipeline = transformers.pipeline(
    "text-generation",
    model="benhaotang/phi4-qwq-sky-t1",
    tokenizer=tokenizer,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a helpful AI asistent. You always think step by step."},
    {"role": "user", "content": "Give me a short intodcution to renormalization group(RG) flow in physcis?"},
]
outputs = pipeline(messages, max_new_tokens=128)
print(outputs[0]["generated_text"])
```

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: prithivMLmods/Phi-4-QwQ
    #no parameters necessary for base model
  - model: benhaotang/Phi-4-llama-t1-full
    parameters:
      density: 0.5
      weight: 0.5
  - model: prithivMLmods/Phi-4-QwQ
    parameters:
      density: 0.5
      weight: 0.5

merge_method: ties
base_model: prithivMLmods/Phi-4-QwQ
parameters:
  normalize: false
  int8_mask: true
dtype: float16
```
# [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/benhaotang__phi4-qwq-sky-t1-details)!
Summarized results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/contents/viewer/default/train?q=benhaotang%2Fphi4-qwq-sky-t1&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!

|      Metric       |Value (%)|
|-------------------|--------:|
|**Average**        |    30.78|
|IFEval (0-Shot)    |     4.60|
|BBH (3-Shot)       |    52.61|
|MATH Lvl 5 (4-Shot)|    39.58|
|GPQA (0-shot)      |    19.35|
|MuSR (0-shot)      |    21.38|
|MMLU-PRO (5-shot)  |    47.16|