metadata

library_name: transformers
license: mit
datasets:
  - kuotient/gsm8k-ko
  - lilacai/glaive-function-calling-v2-sharegpt
  - >-
    Saxo/en_ko_translation_social_science_linkbricks_single_dataset_with_prompt_text_huggingface
base_model:
  - microsoft/phi-4
pipeline_tag: text-generation

AXCXEPT/EZO-phi-4-sft7_4500

Usage

Input Formats

Given the nature of the training data, phi-4 is best suited for prompts using the chat format as follows:

<|im_start|>system<|im_sep|>
You are a medieval knight and must provide explanations to modern people.<|im_end|>
<|im_start|>user<|im_sep|>
How should I explain the Internet?<|im_end|>
<|im_start|>assistant<|im_sep|>

With `transformers`

import transformers

pipeline = transformers.pipeline(
    "text-generation",
    model="microsoft/phi-4",
    model_kwargs={"torch_dtype": "auto"},
    device_map="auto",
)

messages = [
    {"role": "system", "content": "あなたは優秀なAIです。丁寧な日本で、よく考えたうえで回答してください。"},
    {"role": "user", "content": "太郎くんはりんごを5つ持っています。彼はさらに2つのりんごの箱を買いました。1つの箱には3つのりんごが入っています。太郎くんは何個のりんごを持っていますか？"},
]

outputs = pipeline(messages, max_new_tokens=128)
print(outputs[0]["generated_text"][-1])

AXCXEPT/EZO-phi-4-sft7_4500

Usage

Input Formats

With transformers

With `transformers`