181 lines
7.0 KiB
Markdown
181 lines
7.0 KiB
Markdown
---
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license: apache-2.0
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base_model: LiquidAI/LFM2.5-1.2B-Instruct
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- 4-bit
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- 8-bit
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- blackwell-optimized
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- dgx-spark
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- gguf
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- liquid-ai
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- quantized
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- sm121
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---
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---
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## 🚀 v0.1.6: Real-time Metrics & Blackwell-Optimized Docker (Recommended)
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This model is fully compatible with the **[DGX-Spark-llama.cpp-Bench](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)**.
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Experience the state-of-the-art inference engine optimized for NVIDIA Blackwell (DGX Spark) hardware.
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### 🌟 Key Features (v0.1.6)
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- **Real-time Performance Metrics**: Now visualizes `Input TPS` and `Output TPS` during streaming.
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- **Improved Reasoning UI**: Seamlessly renders and stabilizes the model's Chain-of-Thought (CoT).
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- **Blackwell Optimization**: Native support for ARM64/SM121 and CUDA 13.0 FP4.
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### 🐳 Quick Start
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```bash
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# Pull the latest optimized image
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docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.6
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```
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For more details, visit our [GitHub Repository](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench).
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---
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## 🚀 v0.1.6: 실시간 지표 및 Blackwell 최적화 도커 (권장)
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이 모델은 **[DGX-Spark-llama.cpp-Bench](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)** 시스템에 최적화되어 있습니다.
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NVIDIA Blackwell (DGX Spark) 하드웨어의 성능을 최대로 활용하세요.
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### 🌟 주요 특징 (v0.1.6)
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- **실시간 성능 지표 시각화**: 스트리밍 중 `Input TPS` 및 `Output TPS`를 실시간으로 표시합니다.
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- **지능형 추론 UI 고도화**: 모델의 생각하는 과정(CoT)을 더 안정적으로 렌더링합니다.
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- **Blackwell 최적화**: ARM64/SM121 아키텍처 및 CUDA 13.0 FP4 가속 지원.
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### 🐳 실행 방법
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```bash
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# 최신 최적화 이미지 내려받기
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docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.6
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```
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상세한 사용법은 [GitHub 리포지토리](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)를 참조하세요.
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---
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---
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## 🚀 v0.1.5: Real-time Metrics & Blackwell-Optimized Docker (Recommended)
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This model is fully compatible with the **[DGX-Spark-llama.cpp-Bench](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)**.
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Experience the state-of-the-art inference engine optimized for NVIDIA Blackwell (DGX Spark) hardware.
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### 🌟 Key Features (v0.1.5)
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- **Real-time Performance Metrics**: Now visualizes `Input TPS` and `Output TPS` during streaming.
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- **Improved Reasoning UI**: Seamlessly renders and stabilizes the model's Chain-of-Thought (CoT).
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- **Blackwell Optimization**: Native support for ARM64/SM121 and CUDA 13.0 FP4.
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### 🐳 Quick Start
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```bash
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# Pull the latest optimized image
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docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.5
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```
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For more details, visit our [GitHub Repository](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench).
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---
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## 🚀 v0.1.5: 실시간 지표 및 Blackwell 최적화 도커 (권장)
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이 모델은 **[DGX-Spark-llama.cpp-Bench](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)** 시스템에 최적화되어 있습니다.
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NVIDIA Blackwell (DGX Spark) 하드웨어의 성능을 최대로 활용하세요.
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### 🌟 주요 특징 (v0.1.5)
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- **실시간 성능 지표 시각화**: 스트리밍 중 `Input TPS` 및 `Output TPS`를 실시간으로 표시합니다.
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- **지능형 추론 UI 고도화**: 모델의 생각하는 과정(CoT)을 더 안정적으로 렌더링합니다.
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- **Blackwell 최적화**: ARM64/SM121 아키텍처 및 CUDA 13.0 FP4 가속 지원.
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### 🐳 실행 방법
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```bash
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# 최신 최적화 이미지 내려받기
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docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.5
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```
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상세한 사용법은 [GitHub 리포지토리](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)를 참조하세요.
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---
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---
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## 🚀 v0.1.4: Quick Start with Blackwell-Optimized Docker (Recommended)
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This model is fully compatible with the **[DGX-Spark-llama.cpp-Bench](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)**.
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Experience the best performance on NVIDIA Blackwell (DGX Spark) hardware with our optimized inference engine.
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### 🌟 Key Features (v0.1.4)
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- **Blackwell Optimized**: Native support for ARM64/SM121 and CUDA 13.0 FP4.
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- **Intelligent Reasoning UI**: Automatic extraction and visualization of reasoning processes (CoT).
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- **One-Click Deployment**: Standardized environment via GHCR Docker image.
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### 🐳 How to Run
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```bash
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# Pull the latest optimized image
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docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.4
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# Follow the instructions in our repo to serve this model
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# GitHub: https://github.com/sowilow/DGX-Spark-llama.cpp-Bench
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```
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---
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## 🚀 v0.1.4: Blackwell 최적화 도커 퀵스타트 (권장)
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이 모델은 **[DGX-Spark-llama.cpp-Bench](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)** 시스템에 최적화되어 있습니다.
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NVIDIA Blackwell (DGX Spark) 하드웨어의 성능을 최대로 활용하는 최적화된 추론 엔진을 경험해 보세요.
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### 🌟 주요 특징 (v0.1.4)
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- **Blackwell 최적화**: ARM64/SM121 아키텍처 및 CUDA 13.0 FP4 하드웨어 가속 지원.
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- **지능형 추론 UI**: 모델의 생각하는 과정(CoT)을 자동으로 감지하고 시각화합니다.
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- **간편한 배포**: GHCR 도커 이미지를 통해 환경 설정 없이 즉시 실행 가능합니다.
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### 🐳 실행 방법
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```bash
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# 최신 최적화 이미지 내려받기
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docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.4
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```
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상세한 사용법은 [GitHub 리포지토리](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)를 참조하세요.
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---
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---
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## 🚀 Quick Start with Docker (Recommended)
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You can easily run this model using the **DGX-Spark-llama.cpp-Bench** inference engine. It's pre-configured for high-performance inference on NVIDIA hardware (especially Blackwell/DGX Spark).
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### 1. Pull the Docker Image
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```bash
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docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:latest
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```
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### 2. Run the Inference Server
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For detailed configuration and usage, visit the [GitHub Repository](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench).
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---
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# LFM2.5-1.2B-Instruct-DGX-Spark-GGUF
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This repository contains GGUF-quantized weights for **LFM2.5-1.2B-Instruct**, specifically optimized for **NVIDIA Blackwell (DGX Spark)** hardware.
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## 🚀 Key Features
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- **Hardware Optimized**: Built with CUDA 13.0 and SM121 (Blackwell) native acceleration.
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- **Quantization**:
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- **Q4_K_M**: Balanced performance and accuracy.
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- **Q8_0**: High precision preservation.
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- **Base Model Integration**: Linked directly to the original [LiquidAI/LFM2.5-1.2B-Instruct](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct).
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## ⚖️ License & Attribution
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This model is a quantized version of the original [LiquidAI/LFM2.5-1.2B-Instruct](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct) and is subject to its original license.
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## 📂 Files Included
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- `lfm2.5-1.2b-instruct-q4_k_m.gguf`: 4-bit quantized model.
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- `lfm2.5-1.2b-instruct-q8_0.gguf`: 8-bit quantized model.
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---
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*Created using [DGX-Spark-llama.cpp-Bench](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)*
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