Search: “tutorials”

This r/StableDiffusion post addresses one of the most common beginner frustrations in AI image generation: deformed hands and missing or extra fingers are a well-known recurring problem in Stable Diff

This r/ChatGPT post is a community discussion where users share tips on prompting ChatGPT's image generation (via DALL·E) to produce more detailed outputs. The consensus across the community is that c

This Reddit post likely covers common troubleshooting steps for resolving performance issues with ChatGPT, such as clearing browser cache and cookies, disabling browser extensions, and starting a new

This Reddit post addresses a common ChatGPT image generation behavior where the model automatically carries over the seed from a previously generated image, causing new generations to visually resembl

A Reddit post from r/ChatGPT in which a practitioner claims experience building AI prompt systems for real-world investment research shares five common mistakes investors make when using AI for financ

This Reddit post from r/StableDiffusion discusses **metaprompting** — the practice of using LLMs to generate, refine, and optimize Stable Diffusion image prompts, rather than crafting them manually fr

This r/ollama community guide provides a practical breakdown of which AI language models (and combinations of models) can realistically fit within the unified memory constraints of common Apple Silico

This Reddit thread from r/StableDiffusion addresses a common artifact issue with LTX Video 2.3 where generated characters appear duplicated or 'cloned' within the output. The discussion likely covers

This r/StableDiffusion thread discusses community-discovered solutions for preventing quality degradation — such as color drift, flickering, and artifact accumulation — when generating long videos usi

This r/StableDiffusion post likely discusses the community challenge of using OneTrainer — a locally-installed, GUI-based LoRA training tool — to train LoRAs specifically compatible with Z Image (Tong

This r/MachineLearning discussion post argues that LLMs acquire knowledge in a counterintuitive 'backwards' order during training — learning complex, high-level patterns before simpler foundational on

There's so many new techniques like RL, RL LoRA, QLoRA, CPT LoRA. I believe i would have a usecase for them, but i don't know where to learn, youtube is filled with bad quality tutorials if i just sea

Aight, I've given myself a challenge. I want to run Ollama on termux, Seen plenty of tutorials but I'm still confused. Plus, this phone is relatively old, so it might not work. Last time it failed so

This tutorial demonstrates how to use mitmproxy to inspect the actual HTTP traffic sent from a Quarkus application to a local Ollama model via its OpenAI-compatible endpoint, revealing the real JSO...

A beginner-friendly tutorial demonstrating how to build a ~3.2M parameter LLM from scratch using Mary Shelley's *Frankenstein* as the sole training corpus, designed to run on Kaggle's free GPU in u...

Hi Guys, I'm an old coder and DBA that has been in the field for almost 40 years. More and more the jobs I was doing for work are being taken over by AI and the need for my type of work is diminishing

I have to say that I am quite impressed by recent progress in LLM use for coding. I've never really bothered setting up a local model. However now that I went trough some real $$ in Claude / gpt token

You can now automate EDD (eval-driven development) with Coding Harness Agents > build a baseline LLM-based application > score every change with judge evals > keep what improves, reject what regresses

Three weeks back , i posted SHADOW-250M here. It got 360 upvotes, 293 on r/LocalLLaMA and 94 GitHub stars. Thank you. That model was 60 MB, ran around 400 tok/s on CPU and could retrieve records from

Two weeks, one rule, and hundreds of entries from nearly 50 countries. Here's who took the four titles, and a look at everyone who made the final ten! Entries opened August 20 and closed September 1.

So I've been going down a rabbit hole trying to run local LLMs without dropping 800+ on a Mac or GPU. RAM prices are insane right now and I realized that used phones have decent unified memory for dir

Megathread for discussing the release of GLM-5.3-Flash. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comparisons We'll try

I pre-trained a 1.02-billion-parameter on Kimi K3 replica trained on 5.00 billion decontaminated tokens for $250. This model has 1.02 billion parameters, of which 145 million are active per token. It

Hi All, I have a MacBook Pro M5 Max with 48 GB of unified memory. Also have a M4 Mac Mini 16GB unified memory. I want to setup local AI and I heard about QWEN 3.8 model. As I want to work on a repo th

Hi folks, I hate slop as much as you do, so instead of starting with 'The Problem', I'll just cut to the chase: I just published Lophius, which is the culmination of more than two years of fighting wi

Build a 100% offline fast Retrieval Augmented Generation (RAG) system that runs without an internet connection, without cloud APIs, without OpenAI/Ollama Published a video where you can build a fully

Hi everyone! 👋 I built and trained the complete Transformer architecture from scratch using pure PyTorch (`torch.nn` primitives) based on the original 'Attention Is All You Need' paper. I trained the

I wanted to challenge myself and see how far I could push Krea 2 and LTX 2.3, so I decided to create a short cinematic action trailer. It ended up being one of the most enjoyable AI projects I've work