Good question! I am collecting human data on how quantization affects outputs. See here for more information: ggml-org/llama.cpp#5962
In the meantime, use the largest that fully fits in your GPU. If you can comfortably fit Q4_K_S, try using a model with more parameters.
See the wiki upstream: https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix
Detailed Technical Algorithm for a TikTok-like Recommendation System
The objective is to develop a recommendation system that maximizes user engagement by analyzing a multitude of user interaction signals to present the most appealing content. The system optimizes for two key metrics:
| name | llm-council |
|---|---|
| description | Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each other anonymously, and synthesize a final verdict. Based on Karpathy's LLM Council methodology. MANDATORY TRIGGERS: 'council this', 'run the council', 'war room this', 'pressure-test this', 'stress-test this', 'debate this'. STRONG TRIGGERS (use when combined with a real decision or tradeoff): 'should I X or Y', 'which option', 'what would you do', 'is this the right move', 'validate this', 'get multiple perspectives', 'I can't decide', 'I'm torn between'. Do NOT trigger on simple yes/no questions, factual lookups, or casual 'should I' without a meaningful tradeoff (e.g. 'should I use markdown' is not a council question). DO trigger when the user presents a genuine decision with stakes, multiple options, and context that suggests they want it pressure-tested from multiple angles. |
| Last Updated: 7 Oct 2025 | |
| ------------------------- | |
| In this package, you will find a brief introduction to the Scripting API for DaVinci Resolve Studio. Apart from this README.txt file, this package contains folders containing the basic import | |
| modules for scripting access (DaVinciResolve.py) and some representative examples. | |
| From v16.2.0 onwards, the nodeIndex parameters accepted by SetLUT() and SetCDL() are 1-based instead of 0-based, i.e. 1 <= nodeIndex <= total number of nodes. | |
| Overview | |
| -------- | |
| As with Blackmagic Fusion scripts, user scripts written in Lua and Python programming languages are supported. By default, scripts can be invoked from the Console window in the Fusion page, |
| // Based on the Unity Wiki FloatingOrigin script by Peter Stirling | |
| // URL: http://wiki.unity3d.com/index.php/Floating_Origin | |
| using UnityEngine; | |
| using UnityEngine.SceneManagement; | |
| public class FloatingOrigin : MonoBehaviour | |
| { | |
| [Tooltip("Point of reference from which to check the distance to origin.")] | |
| public Transform ReferenceObject = null; |
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| echo "🧹 Resetting CrossOver bottles..." | |
| pkill CrossOver && echo "✅ CrossOver processes killed." | |
| echo "🕒 Modifying trial timestamps..." | |
| DATETIME=$(date -u -v -3H '+%Y-%m-%dT%TZ') | |
| echo "✅ New trial date set to: ${DATETIME}" | |
| defaults write com.codeweavers.CrossOver FirstRunDate -date "${DATETIME}" | |
| defaults write com.codeweavers.CrossOver SULastCheckTime -date "${DATETIME}" | |
| echo "✅ Updated trial timestamps in preferences." | |
| echo "🧹 Resetting CrossOver bottles..." | |
| find ~/Library/Application\ Support/CrossOver/Bottles/ -type f \( -name ".eval" -o -name ".update-timestamp" \) -exec rm -f "{}" + |
