Sparse Training of Neural Networks Using AC/DC
Explore AC/DC, a novel sparse training algorithm for DNNs. Learn its benefits, implementation, and deployment for improved performance and accuracy in deep learning.
Applying Second-Order Pruning Algorithms for SOTA Model Compression
Explore second-order pruning algorithms for model compression, achieving higher sparsity while maintaining accuracy. Learn to apply these techniques to your ML projects for improved efficiency.
Pruning and Quantizing ML Models With One Shot Without Retraining
Adapt advanced pruning and quantization methods for ML models, achieving 4X speedup with 99% accuracy in minutes, using Computer Vision and NLP examples.
Unlock Faster and More Efficient LLMs with SparseGPT - Neural Magic
Optimize LLMs with SparseGPT: prune and quantize models for efficient CPU deployment at GPU speeds. Explore one-shot compression, benchmarks, and practical implementation.
Deploy Fast and Accurate YOLOv8 Object Detection Models on CPUs
Optimize YOLOv8 models for 10x smaller, 8x faster performance on CPUs. Learn sparsification techniques, quantization, and deployment strategies for efficient computer vision applications.
Deploy LLMs More Efficiently with vLLM and Neural Magic
Explore vLLM's efficiency for LLM deployment and Neural Magic's enterprise solutions for cost-effective, scalable AI model services.
Rancher 2.7 Deep Dive - Installation, Features, and GitOps Demo
Explore Rancher 2.7's powerful features: HA installation, cluster management, monitoring, GitOps with Fleet, and RBAC capabilities. Gain hands-on experience with K3s cluster creation and dashboard visualization.
True GitOps Using Crossplane and ArgoCD
Explore GitOps concepts, ArgoCD architecture, and Crossplane benefits. Learn how these tools combine to provide a true GitOps solution through an end-to-end demonstration.
Kubernetes Debugging Techniques - Ephemeral Containers
Explore Kubernetes debugging with ephemeral containers, focusing on troubleshooting distroless and slim images. Learn tips and tricks for effective container management.
Kubernetes CKS Certification Guide 2023 - Exam Preparation and Falco Demo
Explore Kubernetes CKS certification essentials, including exam tips, cloud-native concepts, and Falco security tool. Gain insights and practical knowledge to become a certified Kubernetes security specialist.
All-in-One Kubernetes Observability Using Groundcover
Explore Kubernetes observability with groundcover, an eBPF-based monitoring solution. Learn to quickly identify and resolve issues through five failure scenarios, without instrumentation.
Introducing K2D: Kubernetes to Docker Translator for Industrial IoT
Explore K2D: Kubernetes-to-Docker translator for resource-constrained IoT devices. Learn its creation, advantages, and real-world applications through live demonstrations.
Simplify Add-On Management in Kubernetes with Sveltos
Explore Sveltos, a Kubernetes add-on controller simplifying deployment and management across clusters. Learn from project maintainer Gianluca Mardente about its journey and benefits.
Performing CRUD Operations on Kubernetes Using Golang - API Guide
Learn to perform CRUD operations on Kubernetes resources using Go. Master client libraries, environment setup, and essential operations like reading, creating, updating, and deleting pods.
Embeddings vs Fine-Tuning - Part 1: Understanding and Implementing Embeddings
Explore embedding techniques for language models, including creation, implementation, and performance evaluation. Learn key concepts like semantic search, cosine similarity, and data preparation for optimal results.
Embeddings vs Fine-Tuning - Supervised Fine-tuning - Part 2
Explore supervised fine-tuning techniques for language models. Learn to convert datasets, implement in Google Colab, and compare chat vs base models. Gain practical tips and access to essential scripts.
Advanced Fine-Tuning Techniques for Long Context Summarization
Explore advanced fine-tuning techniques for long context summarization, including increasing rope_theta, training norm and embed, and optimizing prompt-response training for improved model performance.
Serve a Custom LLM for Over 100 Customers - GPU Selection, Quantization, and API Setup
Learn to deploy and serve custom LLMs efficiently for multiple customers. Master server selection, API software, GPU optimization, and quantization techniques for cost-effective, high-performance model serving.
Data Extraction with Large Language Models
Master data extraction techniques using large language models for efficient and accurate information retrieval from various sources. Enhance your skills in JSON and YAML extraction, and compare model performances.
Fine-tuning Optimizations - DoRA, NEFT, LoRA+, and Unsloth
Explore advanced fine-tuning techniques like DoRA, NEFT, LoRA+, and Unsloth to optimize language models. Learn implementation, comparisons, and practical applications through code examples and demonstrations.
Fine-tuning LLMs - Every Step Explained for Memorization Tasks
Explore LLM fine-tuning techniques, from dataset generation to hyperparameter optimization. Learn to overcome challenges like the reversal curse and optimize model performance for specific tasks.