19:11
Your Agent Can Now Train Models — Merve Noyan, Hugging Face
Merve Noyan from the Hugging Face open-source team delivers a broad survey of the current open-model landscape alongside several firs...
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22:54
This 100% uncensored AI model is insane… let’s run it
David Ondrej walks through the rationale, setup, and practical use of uncensored large language models running locally in 2026. The v...
11:12
Qwen3.6 27B Gets 20% Faster with MTP and llama.cpp Locally
Fahd Mirza demonstrates how to enable multi-token prediction (MTP) on Qwen3.6 27B using ik_llama.cpp — a community fork of the popula...
09:01
Running a 27B model at 130 tokens sec on a single GPU Locally with Luce DFlash
LlamaDeFlash is a custom inference engine built from scratch in C++ and CUDA — no vLLM, no llama.cpp, no Python in the critical path...
14:53
This Mutant AI Model Should Not Exist: Qwopus-GLM-18B-Merged Locally
Fahd Mirza walks through the creation and live testing of Qwopus-GLM-18B-Merged, a community-built model that stitches together two s...
09:08
Open WebUI Desktop App – Install on Linux, Windows & Mac
Open WebUI has shipped its first native desktop application for Windows, macOS, and Linux, and Fahd Mirza walks through the complete...
15:26
Gemma, DeepMind’s Family of Open Models — Omar Sanseviero, Google DeepMind
Omar Sanseviero, a researcher at Google DeepMind, delivers the first public conference talk on Gemma 4 just one week after its releas...
15:26
Gemma, DeepMind’s Family of Open Models — Omar Sanseviero, Google DeepMind
Omar Sanseviero, a researcher at Google DeepMind, delivers the first public conference talk on Gemma 4 just one week after its releas...
14:56
MiniMax M2.7 Running Locally on CPU + GPU – Everyone Can Do It
Fahd Mirza walks through the complete process of running MiniMax M2.7 — a newly open-sourced 229-billion-parameter mixture-of-experts...
11:54
Run GLM-5.1 Locally on CPU + GPU Easily: Step-by-Step Tutorial
Fahd Mirza demonstrates how to run GLM-5.1 — the newly open-sourced flagship agentic model from Zhipu AI's GLM team — locally on a si...