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---
license: apache-2.0
language:
- ko
- en
tags:
- text-generation
- pytorch
- causal-lm
- gemma3
- 4b
library_name: transformers
---

# hf_gemma3_4b_2-checkpoint-13000

์ด ๋ชจ๋ธ์€ Gemma3 4B ๋ชจ๋ธ์„ ํŒŒ์ธํŠœ๋‹ํ•œ ์ฒดํฌํฌ์ธํŠธ์ž…๋‹ˆ๋‹ค.

## ๋ชจ๋ธ ์ •๋ณด
- **๋ฒ ์ด์Šค ๋ชจ๋ธ**: hf_gemma3_4b_2
- **์ฒดํฌํฌ์ธํŠธ**: checkpoint-13000
- **๋ชจ๋ธ ํฌ๊ธฐ**: 4B parameters
- **ํƒ€์ž…**: Causal Language Model
- **๋ผ์ด์„ ์Šค**: Apache 2.0

## ์‚ฌ์šฉ ๋ฐฉ๋ฒ•

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "NTIS/hf_gemma3_4b_2-checkpoint-13000"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.float16,
    device_map="auto"
)

# ํ…์ŠคํŠธ ์ƒ์„ฑ
text = "์•ˆ๋…•ํ•˜์„ธ์š”"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(
    **inputs, 
    max_length=100, 
    do_sample=True, 
    temperature=0.7,
    pad_token_id=tokenizer.eos_token_id
)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(result)
```

## ํ›ˆ๋ จ ์ •๋ณด
- ์ด ์ฒดํฌํฌ์ธํŠธ๋Š” ํŠน์ • ์Šคํ…์—์„œ ์ €์žฅ๋œ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค
- ์„ฑ๋Šฅ์€ ์ฒดํฌํฌ์ธํŠธ๋งˆ๋‹ค ๋‹ค๋ฅผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค

## ์ฃผ์˜์‚ฌํ•ญ
- ์ด ๋ชจ๋ธ์€ ์—ฐ๊ตฌ/์‹คํ—˜ ๋ชฉ์ ์œผ๋กœ ์ œ๊ณต๋ฉ๋‹ˆ๋‹ค
- ์ƒ์—…์  ์‚ฌ์šฉ ์ „์— ๋ผ์ด์„ ์Šค๋ฅผ ํ™•์ธํ•˜์„ธ์š”
- GPU ๋ฉ”๋ชจ๋ฆฌ๊ฐ€ ์ถฉ๋ถ„ํ•œ์ง€ ํ™•์ธํ•˜์„ธ์š” (์ตœ์†Œ 8GB ๊ถŒ์žฅ)