README.md

metadata

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

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the TIES merge method using prithivMLmods/Phi-4-QwQ as a base.

Models Merged

The following models were included in the merge:

• benhaotang/Phi-4-llama-t1-full but actually win10/Phi-4-llama-t1-lora, this is who and where you should really thank.
• 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:

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