sowilow/LFM2.5-1.2B-Instruct-DGX-Spark-GGUF
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LFM2.5-1.2B-Instruct-DGX-Sp…/README.md
ModelHub XC 2847e1a464 初始化项目，由ModelHub XC社区提供模型 
Model: sowilow/LFM2.5-1.2B-Instruct-DGX-Spark-GGUF
Source: Original Platform
2026-04-20 19:01:54 +08:00

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license, base_model, language, pipeline_tag, tags
license base_model language pipeline_tag tags
apache-2.0 LiquidAI/LFM2.5-1.2B-Instruct
en
text-generation
4-bit
8-bit
blackwell-optimized
dgx-spark
gguf
liquid-ai
quantized
sm121

🚀 v0.1.6: Real-time Metrics & Blackwell-Optimized Docker (Recommended)

This model is fully compatible with the DGX-Spark-llama.cpp-Bench. Experience the state-of-the-art inference engine optimized for NVIDIA Blackwell (DGX Spark) hardware.

🌟 Key Features (v0.1.6)

  • Real-time Performance Metrics: Now visualizes Input TPS and Output TPS during streaming.
  • Improved Reasoning UI: Seamlessly renders and stabilizes the model's Chain-of-Thought (CoT).
  • Blackwell Optimization: Native support for ARM64/SM121 and CUDA 13.0 FP4.

🐳 Quick Start

# Pull the latest optimized image
docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.6

For more details, visit our GitHub Repository.

🚀 v0.1.6: 실시간 지표 및 Blackwell 최적화 도커 (권장)

이 모델은 DGX-Spark-llama.cpp-Bench 시스템에 최적화되어 있습니다. NVIDIA Blackwell (DGX Spark) 하드웨어의 성능을 최대로 활용하세요.

🌟 주요 특징 (v0.1.6)

  • 실시간 성능 지표 시각화: 스트리밍 중 Input TPS 및 Output TPS를 실시간으로 표시합니다.
  • 지능형 추론 UI 고도화: 모델의 생각하는 과정(CoT)을 더 안정적으로 렌더링합니다.
  • Blackwell 최적화: ARM64/SM121 아키텍처 및 CUDA 13.0 FP4 가속 지원.

🐳 실행 방법

# 최신 최적화 이미지 내려받기
docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.6

상세한 사용법은 GitHub 리포지토리를 참조하세요.

🚀 v0.1.5: Real-time Metrics & Blackwell-Optimized Docker (Recommended)

This model is fully compatible with the DGX-Spark-llama.cpp-Bench. Experience the state-of-the-art inference engine optimized for NVIDIA Blackwell (DGX Spark) hardware.

🌟 Key Features (v0.1.5)

  • Real-time Performance Metrics: Now visualizes Input TPS and Output TPS during streaming.
  • Improved Reasoning UI: Seamlessly renders and stabilizes the model's Chain-of-Thought (CoT).
  • Blackwell Optimization: Native support for ARM64/SM121 and CUDA 13.0 FP4.

🐳 Quick Start

# Pull the latest optimized image
docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.5

For more details, visit our GitHub Repository.

🚀 v0.1.5: 실시간 지표 및 Blackwell 최적화 도커 (권장)

이 모델은 DGX-Spark-llama.cpp-Bench 시스템에 최적화되어 있습니다. NVIDIA Blackwell (DGX Spark) 하드웨어의 성능을 최대로 활용하세요.

🌟 주요 특징 (v0.1.5)

  • 실시간 성능 지표 시각화: 스트리밍 중 Input TPS 및 Output TPS를 실시간으로 표시합니다.
  • 지능형 추론 UI 고도화: 모델의 생각하는 과정(CoT)을 더 안정적으로 렌더링합니다.
  • Blackwell 최적화: ARM64/SM121 아키텍처 및 CUDA 13.0 FP4 가속 지원.

🐳 실행 방법

# 최신 최적화 이미지 내려받기
docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.5

상세한 사용법은 GitHub 리포지토리를 참조하세요.

🚀 v0.1.4: Quick Start with Blackwell-Optimized Docker (Recommended)

This model is fully compatible with the DGX-Spark-llama.cpp-Bench. Experience the best performance on NVIDIA Blackwell (DGX Spark) hardware with our optimized inference engine.

🌟 Key Features (v0.1.4)

  • Blackwell Optimized: Native support for ARM64/SM121 and CUDA 13.0 FP4.
  • Intelligent Reasoning UI: Automatic extraction and visualization of reasoning processes (CoT).
  • One-Click Deployment: Standardized environment via GHCR Docker image.

🐳 How to Run

# Pull the latest optimized image
docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.4

# Follow the instructions in our repo to serve this model
# GitHub: https://github.com/sowilow/DGX-Spark-llama.cpp-Bench

🚀 v0.1.4: Blackwell 최적화 도커 퀵스타트 (권장)

이 모델은 DGX-Spark-llama.cpp-Bench 시스템에 최적화되어 있습니다. NVIDIA Blackwell (DGX Spark) 하드웨어의 성능을 최대로 활용하는 최적화된 추론 엔진을 경험해 보세요.

🌟 주요 특징 (v0.1.4)

  • Blackwell 최적화: ARM64/SM121 아키텍처 및 CUDA 13.0 FP4 하드웨어 가속 지원.
  • 지능형 추론 UI: 모델의 생각하는 과정(CoT)을 자동으로 감지하고 시각화합니다.
  • 간편한 배포: GHCR 도커 이미지를 통해 환경 설정 없이 즉시 실행 가능합니다.

🐳 실행 방법

# 최신 최적화 이미지 내려받기
docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:v0.1.4

상세한 사용법은 GitHub 리포지토리를 참조하세요.

🚀 Quick Start with Docker (Recommended)

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).

1. Pull the Docker Image

docker pull ghcr.io/sowilow/dgx-spark-llama.cpp-bench:latest

2. Run the Inference Server

For detailed configuration and usage, visit the GitHub Repository.

LFM2.5-1.2B-Instruct-DGX-Spark-GGUF

This repository contains GGUF-quantized weights for LFM2.5-1.2B-Instruct, specifically optimized for NVIDIA Blackwell (DGX Spark) hardware.

🚀 Key Features

  • Hardware Optimized: Built with CUDA 13.0 and SM121 (Blackwell) native acceleration.
  • Quantization:
    • Q4_K_M: Balanced performance and accuracy.
    • Q8_0: High precision preservation.
  • Base Model Integration: Linked directly to the original LiquidAI/LFM2.5-1.2B-Instruct.

⚖️ License & Attribution

This model is a quantized version of the original LiquidAI/LFM2.5-1.2B-Instruct and is subject to its original license.

📂 Files Included

  • lfm2.5-1.2b-instruct-q4_k_m.gguf: 4-bit quantized model.
  • lfm2.5-1.2b-instruct-q8_0.gguf: 8-bit quantized model.

Created using DGX-Spark-llama.cpp-Bench