commit c70b49eb5b6fc4b2772dd34bc60fe6f9f4d22d51
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Mon Apr 20 09:03:16 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: gyung/lfm2-1.2b-koen-mt-v4-100k-GGUF
    Source: Original Platform

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+lfm2-1.2b-koen-mt-v4-100k-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
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diff --git a/README.md b/README.md
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+---
+license: other
+license_name: lfm-open-license-v1.0
+license_link: https://huggingface.co/LiquidAI/LFM2-1.2B/blob/main/LICENSE
+language:
+- ko
+- en
+pipeline_tag: translation
+tags:
+- lfm2
+- liquid-ai
+- korean
+- gguf
+- quantization
+base_model: gyung/lfm2-1.2b-koen-mt-v4-100k
+---
+
+# 🌊 LFM2-1.2B-KoEn-MT-v4-100k-GGUF
+
+이 리포지토리는 [gyung/lfm2-1.2b-koen-mt-v4-100k](https://huggingface.co/gyung/lfm2-1.2b-koen-mt-v4-100k) 모델의 **GGUF(Gemma/Llama.cpp Compatible)** 양자화 버전을 포함하고 있습니다.
+
+## ℹ️ 모델 설명 (Model Description)
+
+**LFM2-1.2B-KoEn-MT-v4-100k**은 LiquidAI의 `LFM2-1.2B` 아키텍처를 기반으로 한국어-영어 번역 성능을 극대화하기 위해 **100,000개의 고품질 병렬 데이터셋**으로 파인튜닝된 모델입니다.
+
+* **Base Model**: LiquidAI/LFM2-1.2B
+* **Finetuned by**: Gyung
+* **Parameters**: 1.2B
+* **Purpose**: Korean-English Translation (한국어-영어 번역)
+
+## 📦 제공되는 GGUF 파일 (Quantization Methods)
+
+사용 환경과 필요에 따라 적절한 양자화 버전을 선택하여 다운로드하세요. (권장: `Q4_K_M` 또는 `Q5_K_M`)
+
+| 파일명 (예시) | 양자화 (Quant) | 크기 (Size) | 설명 (Description) |
+| --- | --- | --- | --- |
+| `lfm2-1.2b-koen-mt-v4-100k-f16.gguf` | F16 | ~2.34 GB | 원본 성능 유지, 용량 큼 |
+| `lfm2-1.2b-koen-mt-v4-100k-q8_0.gguf` | Q8_0 | ~1.25 GB | 품질 손실 거의 없음 |
+| `lfm2-1.2b-koen-mt-v4-100k-q6_k.gguf` | Q6_K | ~963 MB | 높은 품질, 균형 잡힌 성능 |
+| `lfm2-1.2b-koen-mt-v4-100k-q5_k_m.gguf` | Q5_K_M | ~843 MB | **추천**: 품질과 속도/용량의 최적 균형 |
+| `lfm2-1.2b-koen-mt-v4-100k-q4_k_m.gguf` | Q4_K_M | ~731 MB | **추천**: 적은 메모리 소모, 준수한 성능 |
+| `lfm2-1.2b-koen-mt-v4-100k-q4_0.gguf` | Q4_0 | ~696 MB | 가장 가벼움, 일부 품질 저하 가능성 |
+
+## 🚀 사용 방법 (Usage)
+
+### llama.cpp
+
+최신 버전의 `llama.cpp`를 사용하여 실행할 수 있습니다. (LFM 아키텍처 지원 여부를 확인하세요)
+
+```bash
+./llama-cli -m lfm2-1.2b-koen-mt-v4-100k-q5_k_m.gguf \
+  -p "Translate to Korean: The model is working correctly now." \
+  -n 256
+````
+
+### Python (llama-cpp-python)
+
+```python
+from llama_cpp import Llama
+
+llm = Llama(
+    model_path="./lfm2-1.2b-koen-mt-v4-100k-q5_k_m.gguf",
+    n_ctx=2048,
+    verbose=False
+)
+
+prompt = "Translate to Korean: The model is working correctly now."
+output = llm(
+    f"User: {prompt}\nAssistant:",
+    max_tokens=256,
+    stop=["User:", "\n"],
+    echo=True
+)
+
+print(output['choices'][0]['text'])
+```
+
+## 📊 벤치마크 (Benchmarks)
+
+원본 모델(F16) 기준 **Flores-200** 평가 결과입니다. GGUF 양자화 시 점수는 소폭 하락할 수 있습니다.
+
+  * **LFM2-1.2B-KOEN-MT-v4-100k**: CHrF++ **30.98** / BLEU **11.09**
+  * Google Translate: CHrF++ 39.27
+  * NLLB-200-Distilled-600M: CHrF++ 31.97
+
+## 📜 라이선스 (License)
+
+이 모델은 **Liquid AI LFM Open License v1.0**을 따릅니다.
+
+  * 학술/개인 연구: 제한 없음
+  * 상업적 이용: 연 매출 $10M 미만 무료 (초과 시 별도 계약 필요)
+  * 자세한 내용은 [LICENSE](https://huggingface.co/LiquidAI/LFM2-1.2B/blob/main/LICENSE)를 참고하세요.
+
+## Citation
+
+```bibtex
+@misc{lfm2-1.2b-koen-mt-v4-100k,
+  author = {Gyung},
+  title = {LFM2-1.2B Korean-English Machine Translation Model v4},
+  year = {2025},
+  publisher = {Hugging Face},
+  journal = {Hugging Face Model Hub},
+  howpublished = {\url{[https://huggingface.co/gyung/lfm2-1.2b-koen-mt-v4-100k](https://huggingface.co/gyung/lfm2-1.2b-koen-mt-v4-100k)}}
+}
+```
\ No newline at end of file
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