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Usage:

Sejong-Qwen-v4_inference.ipynb: Open In Colab

!pip install transformers einops accelerate
!pip install qwen
!pip install unsloth

from transformers import AutoTokenizer, AutoModelForCausalLM

# ν† ν¬λ‚˜μ΄μ €μ™€ λͺ¨λΈ λ‘œλ“œ
tokenizer = AutoTokenizer.from_pretrained(
    "SejongKRX/Sejong-Qwen-4",
    trust_remote_code=True,
    use_fast=False
)
model = AutoModelForCausalLM.from_pretrained(
    "SejongKRX/Sejong-Qwen-4",
    trust_remote_code=True
)

# μž…λ ₯ ν…μŠ€νŠΈ
input_text =  """
λ‹€μŒ 쀑 ν™”νμ˜ μ‹œκ°„κ°€μΉ˜μ— κ΄€ν•œ μ„€λͺ…μœΌλ‘œ μ˜³μ§€ μ•Šμ€ 것은 무엇인가?

A. μ›” 볡리의 경우, 맀월 μ μš©λ˜λŠ” μ΄μžμœ¨μ€ μ—°κ°„ λͺ…λͺ© μ΄μžμœ¨μ„ 1/12둜 λ‚˜λˆ„μ–΄ μ‚°μΆœν•œλ‹€.
B. 투자 μ›κΈˆ 및 기타 쑰건이 동일할 경우, 단리 방식보닀 볡리 λ°©μ‹μ—μ„œ λ°œμƒν•˜λŠ” μ΄μžκ°€ 더 크닀.
C. μΌμ‹œλΆˆλ‘œ 지급될 κΈˆμ•‘μ˜ ν˜„μž¬ κ°€μΉ˜λŠ” 미래 κ°€μΉ˜λ₯Ό 일정 κΈ°κ°„ λ™μ•ˆ ν• μΈμœ¨μ„ μ μš©ν•΄ μ‚°μΆœν•  수 μžˆλ‹€.
D. 1,000,000원을 μ—° 5% 볡리둜 2λ…„ λ™μ•ˆ μ˜ˆμΉ˜ν–ˆμ„ 경우, λ§ŒκΈ°μ— 받을 μ„Έμ „ μ΄μžλŠ” 100,000원이닀.

### μ •λ‹΅:
"""

inputs = tokenizer(input_text, return_tensors="pt")

# λͺ¨λΈμ„ μ‚¬μš©ν•˜μ—¬ ν…μŠ€νŠΈ 생성
output = model.generate(**inputs, max_new_tokens=1500)

# κ²°κ³Ό λ””μ½”λ”©
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
print(generated_text)

output:

λ‹€μŒ 쀑 ν™”νμ˜ μ‹œκ°„κ°€μΉ˜μ— κ΄€ν•œ μ„€λͺ…μœΌλ‘œ μ˜³μ§€ μ•Šμ€ 것은 무엇인가?

A. μ›” 볡리의 경우, 맀월 μ μš©λ˜λŠ” μ΄μžμœ¨μ€ μ—°κ°„ λͺ…λͺ© μ΄μžμœ¨μ„ 1/12둜 λ‚˜λˆ„μ–΄ μ‚°μΆœν•œλ‹€.
B. 투자 μ›κΈˆ 및 기타 쑰건이 동일할 경우, 단리 방식보닀 볡리 λ°©μ‹μ—μ„œ λ°œμƒν•˜λŠ” μ΄μžκ°€ 더 크닀.
C. μΌμ‹œλΆˆλ‘œ 지급될 κΈˆμ•‘μ˜ ν˜„μž¬ κ°€μΉ˜λŠ” 미래 κ°€μΉ˜λ₯Ό 일정 κΈ°κ°„ λ™μ•ˆ ν• μΈμœ¨μ„ μ μš©ν•΄ μ‚°μΆœν•  수 μžˆλ‹€.
D. 1,000,000원을 μ—° 5% 볡리둜 2λ…„ λ™μ•ˆ μ˜ˆμΉ˜ν–ˆμ„ 경우, λ§ŒκΈ°μ— 받을 μ„Έμ „ μ΄μžλŠ” 100,000원이닀.

### μ •λ‹΅:
D

Dataset

λ³Έ λͺ¨λΈμ€ λ‹€μ–‘ν•œ 좜처의 데이터(mlabonne/open-perfectblend, Wikipedia, ν•œκ΅­μ€ν–‰μ˜ 곡곡 데이터 λ“±)λ₯Ό ν™œμš©ν•˜μ—¬ ν•™μŠ΅λ˜μ—ˆμœΌλ©°, λͺ¨λ“  λ°μ΄ν„°λŠ” μ €μž‘κΆŒ 및 μ‚¬μš© 정책에 따라 적절히 μ‚¬μš©λ˜μ—ˆμŠ΅λ‹ˆλ‹€.

  • Wikipedia λ°μ΄ν„°λŠ” CC BY-SA 4.0 λΌμ΄μ„ μŠ€λ₯Ό λ”°λ¦…λ‹ˆλ‹€. μžμ„Έν•œ μ •λ³΄λŠ” μ—¬κΈ°μ—μ„œ 확인할 수 μžˆμŠ΅λ‹ˆλ‹€.
  • ν•œκ΅­μ€ν–‰μ˜ λ°μ΄ν„°λŠ” ν•œκ΅­μ€ν–‰μ˜ μ €μž‘κΆŒ λ³΄ν˜Έλ°©μΉ¨μ— 따라 μ‚¬μš©λ˜μ—ˆμŠ΅λ‹ˆλ‹€.
  • mlabonne/open-perfectblend λ°μ΄ν„°λŠ” Apache 2.0 λΌμ΄μ„ μŠ€λ₯Ό λ”°λ¦…λ‹ˆλ‹€. λΌμ΄μ„ μŠ€μ— λŒ€ν•œ μžμ„Έν•œ λ‚΄μš©μ€ Apache 2.0 λΌμ΄μ„ μŠ€μ—μ„œ 확인할 수 μžˆμŠ΅λ‹ˆλ‹€.

Uploaded model

  • Developed by: SejongKRX
  • License: apache-2.0
  • Finetuned from model : unsloth/qwen2.5-7b

This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.

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