#DeepSpeed ZeRO
27 related articles
·3 min
Fine-Tuning 8B LLMs on a 4GB GPU: A Deep Dive into VRAM Optimization Techniques
Learn how to fine-tune 8B parameter LLMs on a 4GB laptop GPU using QLoRA quantization, gradient checkpointing, and gradient accumulation VRAM optimization techniques.
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·3 min
Training a 1.3B Parameter LLM from Scratch: Complete Workflow and Core Challenges
A deep dive into the complete workflow of training a 1.3B parameter LLM from scratch, covering Transformer architecture design, data preparation, and distributed training optimization.
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·3 min
Dual RTX 3060 Running DeepSeek V4 Flash: IQ2_M Quantized Inference Benchmarked at 3.5 tok/s
Benchmarking DeepSeek V4 Flash on dual RTX 3060 GPUs with 96GB RAM at IQ2_M quantization achieving 3.5 tokens/sec. Covers hardware choices, 2-bit quantization techniques, and local LLM deployment optimization.
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·5 min
The Complete Learning Path to Understanding the Kimi K3 Technical Report
A systematic learning path for understanding the Kimi K3 technical report, covering MoE, MLA, distributed training, and modern post-training techniques.
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JAX Host Offloading: A Practical Guide…
·2 min
JAX Host Offloading: A Practical Guide to Breaking Through LLM Training Memory Bottlenecks
Memory capacity is the core bottleneck in LLM training. This guide explores JAX-based host offloading — covering optimizer state offloading, activation strategies, PCIe bandwidth trade-offs, and how it complements activation recomputation.
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·2 min
Distributed AI Systems: A Practical Engineering Guide to Training, Inference, and Production Deployment
A deep dive into distributed AI systems engineering: data/model/tensor parallelism for training, KV cache, quantization, elastic scaling for inference, and cloud deployment with Kubernetes, Ray, and DeepSpeed.
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·5 min
Nonuniform Tensor Parallelism: NVIDIA's New Fault-Tolerance Approach to Boost LLM Training Goodput
NVIDIA introduces Nonuniform Tensor Parallelism, letting GPUs bear different compute loads so training can continue without checkpoint rollback during hardware failures—boosting LLM training Goodput and fault tolerance at scale.
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·5 min
Reproducing GitHub Projects from Scratch: A Practical Step-by-Step Guide
A complete guide to reproducing GitHub projects from scratch: due diligence, virtual environments, dependency installation, script interpretation, and breakpoint debugging — helping grad students and junior developers run others' code efficiently.
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·2 min
A Complete Guide to LLM Infrastructure: Core Challenges from GPU Clusters to Inference Optimization
A deep dive into core challenges and key technologies for LLM infrastructure, covering GPU cluster management, inference optimization, distributed training, cost control, and observability.
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Tutorials·2 min
Gemma 4 Complete Guide: The Apache 2.0 Open-Source Agent Powerhouse
In-depth analysis of Google's Gemma 4 open-source models: 31B, 26B MOE, and 14B/12B benchmarks, deployment guides for all platforms, and MS-Swift fine-tuning tutorial for building local Agent workflows.
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Tutorials·2 min
Hermes + Qwen3.6 Local Deployment Tutorial: Build Your Private AI Agent at Zero Cost
Step-by-step tutorial to deploy Hermes Agent with Qwen3.6 open-source LLM locally. Covers WSL setup, model download, Telegram bot integration for a zero-cost private AI Agent.
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Tutorials·4 min
NCCL Inspector Explained: Real-Time GPU Cluster Communication Monitoring with Prometheus Integration
Deep dive into NVIDIA NCCL Inspector for real-time GPU cluster communication monitoring with Prometheus integration, covering straggler detection, alerting, and Grafana visualization for distributed training optimization.
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Product Reviews·4 min
Cube Studio Deep Dive: Tencent's Open-Source One-Stop MLOps Platform
Deep dive into Cube Studio, Tencent Music's open-source one-stop AI platform, covering architecture design, distributed training, large model fine-tuning and inference, and domestic chip adaptation.
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Product Reviews·3 min
Cube Studio: A Comprehensive Analysis of Tencent's Open-Source Cloud-Native AI Platform
Deep dive into Tencent Music's open-source Cube Studio cloud-native AI platform, covering distributed training, LLM fine-tuning & inference, Pipeline orchestration, and domestic hardware adaptation.
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Product Reviews·3 min
Cube Studio: Tencent's Open-Source One-Stop AI Platform — A Deep Dive into Full MLOps Lifecycle
Deep dive into Tencent Music's open-source Cube Studio cloud-native AI platform, covering Notebook development, Pipeline orchestration, distributed training, LLM fine-tuning, inference deployment, and domestic hardware adaptation for full MLOps lifecycle.
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Product Reviews·3 min
GitHub 8000+ Stars: A Deep Dive into awesome-LLM-resources — The Most Comprehensive Large Language Model Resource Collection
Deep dive into the GitHub 8000+ star project awesome-LLM-resources, covering LLM training, multimodal generation, AI Agents, MCP protocol, AI-assisted coding, and more for developers.
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Product Reviews·4 min
Cube Studio: Tencent's Open-Source All-in-One AI Platform Covering the Full Pipeline from Large Model Training to Inference
Deep dive into Tencent Music's open-source Cube Studio cloud-native AI platform, covering distributed training, LLM fine-tuning, vLLM inference, VGPU virtualization, and Huawei Ascend adaptation.
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Product Reviews·3 min
awesome-LLM-resources: Deep Dive into a GitHub 8000+ Star LLM Resource Collection
Deep dive into GitHub's 8000+ star project awesome-LLM-resources, covering AI Agents, model training, MCP protocol, multimodal generation and more across 10 core LLM directions.
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Product Reviews·4 min
Deep Dive into Cube Studio: Tencent's Open-Source All-in-One AI Platform
Deep dive into Tencent's open-source AI platform Cube Studio, covering distributed training, large model fine-tuning and inference, Pipeline orchestration, VGPU virtualization, and Huawei Ascend support for enterprise cloud-native MLOps.
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Product Reviews·4 min
Cube Studio Deep Dive: Tencent's Open-Source One-Stop Cloud-Native AI Platform
Deep dive into Tencent's open-source AI platform Cube Studio, covering distributed training, LLM fine-tuning, inference deployment, VGPU virtualization, and domestic hardware support for enterprise MLOps.
Read more →