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infrastructure#llm📝 BlogAnalyzed: Jan 18, 2026 12:45

Unleashing AI Creativity: Local LLMs Fueling ComfyUI Image Generation!

Published:Jan 18, 2026 12:31
1 min read
Qiita AI

Analysis

This is a fantastic demonstration of combining powerful local language models with image generation tools! Utilizing a DGX Spark with 128GB of integrated memory opens up exciting possibilities for AI-driven creative workflows. This integration allows for seamless prompting and image creation, streamlining the creative process.
Reference

“With the 128GB of integrated memory on the DGX Spark I purchased, it's possible to run a local LLM while generating images with ComfyUI. Amazing!”

PermalinkQiita AI
infrastructure#llm📝 BlogAnalyzed: Jan 11, 2026 00:00

Setting Up Local AI Chat: A Practical Guide

Published:Jan 10, 2026 23:49
1 min read
Qiita AI

Analysis

This article provides a practical guide for setting up a local LLM chat environment, which is valuable for developers and researchers wanting to experiment without relying on external APIs. The use of Ollama and OpenWebUI offers a relatively straightforward approach, but the article's limited scope ("動くところまで") suggests it might lack depth for advanced configurations or troubleshooting. Further investigation is warranted to evaluate performance and scalability.
Reference

“まずは「動くところまで」”

PermalinkQiita AI
AI Research#LLM Frontend, OCR, Token Probabilities📝 BlogAnalyzed: Jan 3, 2026 06:31

Frontend Tools for Viewing Top Token Probabilities

Published:Jan 3, 2026 00:11
1 min read
r/LocalLLaMA

Analysis

The article discusses the need for frontends that display top token probabilities, specifically for correcting OCR errors in Japanese artwork using a Qwen3 vl 8b model. The user is looking for alternatives to mikupad and sillytavern, and also explores the possibility of extensions for popular frontends like OpenWebUI. The core issue is the need to access and potentially correct the model's top token predictions to improve accuracy.
Reference

“I'm using Qwen3 vl 8b with llama.cpp to OCR text from japanese artwork, it's the most accurate model for this that i've tried, but it still sometimes gets a character wrong or omits it entirely. I'm sure the correct prediction is somewhere in the top tokens, so if i had access to them i could easily correct my outputs.”

Permalinkr/LocalLLaMA