Update README.md

README.md

@@ -1,199 +1,171 @@
 ---
-library_name: transformers
-tags: []
+license: apache-2.0
+base_model: kakaocorp/kanana-safeguard-siren-8b
+quantized_by: Arc1el
+quantization_method: bitsandbytes
+model_type: llama
+tags:
+- quantized
+- 4bit
+- bitsandbytes
+- safeguard
+- korean
+- safety
+pipeline_tag: text-generation
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
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-## Uses
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-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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-### Direct Use
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-## How to Get Started with the Model
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-Use the code below to get started with the model.
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+# Kanana Safeguard Siren 8B - 4bit 양자화 버전
+
+## 모델 개요
+- **원본 모델**: [kakaocorp/kanana-safeguard-siren-8b](https://huggingface.co/kakaocorp/kanana-safeguard-siren-8b)
+- **양자화 방법**: BitsAndBytes 4bit (NF4)
+- **양자화 도구**: bitsandbytes + transformers
+- **압축률**: 원본 대비 약 75% 크기 감소 (추정)
+
+## 모델 세부정보
+
+### 원본 모델 정보
+- **모델 아키텍처**: Safeguard model based on transformer architecture
+- **파라미터 수**: 8B parameters
+- **주요 용도**: 안전성 검증, 유해 콘텐츠 탐지
+- **언어**: 한국어 중심
+- **원본 모델 라이선스**: Apache 2.0
+
+### 양자화 정보
+- **양자화 타입**: 4bit NormalFloat (NF4)
+- **정밀도**: 4bit weights, 16bit activations
+
+## 성능 및 벤치마크
+
+### 모델 크기 비교
+- **원본 모델**: ~16GB (추정)
+- **양자화 모델**: ~4GB (추정)
+- **압축률**: 약 75% 감소
+
+### 메모리 사용량
+- **로딩 시 VRAM**: 약 4-5GB
+- **추론 시 VRAM**: 약 6-8GB (배치 크기에 따라 변동)
+- **시스템 RAM**: 최소 8GB 권장
+
+## 사용법
+
+### 설치
+```bash
+pip install transformers accelerate bitsandbytes torch
+```
+
+### 코드 예시
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+
+model_name = "[your-username]/kanana-safeguard-siren-8b-4bit"
+
+# BitsAndBytesConfig 설정
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.bfloat16
+)
+
+# 모델과 토크나이저 로드
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    quantization_config=bnb_config,
+    device_map="auto",
+    trust_remote_code=True
+)
+
+# 사용 예시 - 안전성 검증
+text = "이것은 검증할 텍스트입니다."
+inputs = tokenizer(text, return_tensors="pt")
+
+with torch.no_grad():
+    outputs = model.generate(
+        **inputs,
+        max_length=512,
+        temperature=0.7,
+        do_sample=True,
+        pad_token_id=tokenizer.eos_token_id
+    )
+
+result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(result)
+```
+
+## 시스템 요구사항
+- **최소 RAM**: 8GB
+- **권장 RAM**: 16GB
+- **GPU 메모리**: 6GB VRAM (RTX 3060 이상)
+- **지원 플랫폼**: Linux, Windows (CUDA 지원 GPU)
+- **Python**: 3.8+
+- **CUDA**: 11.1+
+
+## 제한사항 및 고려사항
+
+### 성능 제한사항
+- 4bit 양자화로 인한 미미한 성능 저하 가능
+- 원본 모델 대비 추론 품질이 약간 감소할 수 있음
+- 복잡한 안전성 판단에서 더 큰 영향을 받을 수 있음
+
+### 사용 권장사항
+- GPU 메모리 제약이 있는 환경에서 사용 권장
+- 실시간 안전성 검증이 필요한 애플리케이션에 적합
+- 프로덕션 환경 사용 전 충분한 검증 필요
+
+### 주의사항
+- 이 모델은 안전성 검증 목적의 safeguard 모델입니다
+- 원본 모델의 성능과 안전성 특성을 양자화 후에도 유지하도록 노력했으나, 완전히 동일하지 않을 수 있습니다
+- 중요한 안전성 판단에는 원본 모델과의 교차 검증을 권장합니다
+
+## 윤리적 고려사항
+- 원본 Kakao Corp의 safeguard 모델의 윤리적 가이드라인을 준수합니다
+- 이 모델은 유해 콘텐츠 탐지 및 안전성 검증 목적으로만 사용되어야 합니다
+- 양자화로 인한 예상치 못한 편향이나 안전성 이슈가 발생할 수 있으므로 주의가 필요합니다
+
+## 라이선스
+이 양자화 모델은 원본 모델과 동일한 **Apache License 2.0**을 따릅니다.
+
+```
+Copyright 2025 Kakao Corp. (Original model)
+Copyright 2025 [Your Name] (Quantization)
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+```
+
+## 크레딧 및 인용
+
+### 원본 모델 크레딧
+```bibtex
+@misc{kakao-kanana-safeguard-siren-8b,
+  title={Kanana Safeguard Siren 8B},
+  author={Kakao Corp},
+  year={2024},
+  publisher={Hugging Face},
+  url={https://huggingface.co/kakaocorp/kanana-safeguard-siren-8b}
+}
+```
+
+### 양자화 버전 인용
+```bibtex
+@misc{kakao-kanana-safeguard-siren-8b-4bit,
+  title={Kanana Safeguard Siren 8B - 4bit Quantized},
+  author={[Your Name]},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/nxtcloud-org/kanana-safeguard-siren-8b-4bit},
+  note={4bit quantization of kakaocorp/kanana-safeguard-siren-8b using bitsandbytes}
+}
+```