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Beyond the GGUF Era: A New Horizon in Local AI Research with DGX Spark

This post explores a new horizon in local AI research using DGX Spark beyond the GGUF model. It introduces the latest Flux model, methods for building local environments, performance comparisons, and practical usage cases.

The New Standard for Storing AI Models: Concepts and Advantages

Introducing the new standard format for storing AI models, .safetensors, and detailing its concepts and advantages. This post discusses the benefits and use cases of the .safetensors format.

Complete Guide to GGUF Format - The New Standard for Local LLMs

The GGUF format is the new standard for efficiently storing and deploying local LLM models. This guide details the structure, conversion methods, use cases, and advantages of the GGUF format and provides step-by-step instructions for utilizing it in local LLM environments.

The Secret of LoRA Model Updates - Techniques of Fine-Tuning Similar to Human Memory: Forgetting and Review

Explore the secrets of LoRA model updates, introducing fine-tuning techniques that mimic human memory through mechanisms of forgetting and review. This post addresses effective update strategies and practical applications for LoRA-based models, offering valuable insights for AI developers and researchers.

Analysis of FLUX1-dev 12B LoRA Fine-tuning Results - 250 vs 1000 Steps, Who is the Winner?

This post analyzes the performance differences between 250 and 1000 steps in fine-tuning the FLUX1-dev 12B model with LoRA. It presents the optimal step count based on learning speed, memory usage, and final performance indicators while summarizing the pros and cons of LoRA fine-tuning.

Practical Experience of Fine-Tuning FLUX 1-dev 12B LoRA on DGX Spark - The Light and Dark of Low-Power, High-Efficiency Training

Sharing practical experience of fine-tuning the FLUX 1-dev 12B model on ARM-based DGX Spark. Detailed analysis of the learning process including 1000 Steps, 100 Epochs, OOM issues, power efficiency, and CPU bottlenecks, along with future improvement plans.

The Key to Efficient AI Fine-Tuning - A Comprehensive Guide to LoRA

This blog post summarizes how to efficiently fine-tune using LoRA (Low-Rank Adaptation) in the era of large language models. It highlights the principles, advantages, and practical applications of the PEFT technique.

The Hidden Ally of Image Generation Models - CLIP and Advanced Prompt Strategies

This article introduces strategies for optimizing image generation prompts using CLIP and dual encoders. It explains the roles of T5-XXL and CLIP-L and how to effectively combine sentences and keywords for high-quality image creation.

AI Voice Recognition War: Whisper vs Parakeet – Who's the Winner of Real-Time Transcription?

We compare NVIDIA's new voice recognition model Parakeet with Whisper, analyzing the speed, accuracy, and potential applications of real-time AI transcription technology.