andyg5000

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andyg5000

andyg5000

@AndyG5000

Founder: Blue Oak Interactive, Drupal Development Co-Founder: Dripyard, Premium Drupal Themes Founder: Secret Sounds, Live Audio/Video Recording

USA Katılım Ağustos 2008
165 Takip Edilen307 Takipçiler
andyg5000
andyg5000@AndyG5000·
@UnslothAI any plans to roll a linux/arm64/v8 compatible version of studio for docker? I'm trying to run it on a gx10/dgx spark.
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glitch
glitch@glitch_·
hermes agent and qwen 27b feels unmatched
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andyg5000
andyg5000@AndyG5000·
@sudoingX Tried this today and had a lot of issues using qwen 3.5 (3090) and nemotron (dgx) Biggest problem was loops of responses when asking to create simple reminders. I'm just using local llm option, but something is missing
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Sudo su
Sudo su@sudoingX·
I will help anyone migrate from openclaw slop bloat to Hermes agent, the majestic agent, the only one you will ever need. You deserve better tools in this changing landscape. Let's do an upgrade to your setup, anon.
Neo@NeoAIForecast

@sudoingX I am fully migrated from openclaw now!

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andyg5000
andyg5000@AndyG5000·
@nmdmatt Congrats on this! I recommend this for anyone doing web development, not just Drupal. It covers a lot of techniques within Drupal, but also beyond the PHP request/response cycle. It's insane how powerful the Drupal caching stack is and this is a DEEEEP dive 😀
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Matt Glaman
Matt Glaman@nmdmatt·
My book Understanding #Drupal: A Complete Guide to Caching Layers is now published on LeanPub! Covers the full stack — render pipeline, cache backends, HTTP headers, reverse proxies, and writing cacheable code. mglaman.dev/blog/understan…
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Numman Ali
Numman Ali@nummanali·
Claude Code teams with tmux is really cool When you run with team mode enabled in tmux, it automatically opens the additional terminal in pane I don't really get my main agent to orchestrate, I chat to them myself CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=true claude
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GREG ISENBERG
GREG ISENBERG@gregisenberg·
karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo github.com/karpathy/autor… for your to mess around with it in the latest episode of @startupideaspod i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch
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Andrej Karpathy
Andrej Karpathy@karpathy·
@nummanali tmux grids are awesome, but i feel a need to have a proper "agent command center" IDE for teams of them, which I could maximize per monitor. E.g. I want to see/hide toggle them, see if any are idle, pop open related tools (e.g. terminal), stats (usage), etc.
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andyg5000
andyg5000@AndyG5000·
How many people actually know what @karpathy's autoresearch actually does vs just vibing off the name and creating click-bait for the next hot business idea?
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andyg5000
andyg5000@AndyG5000·
@harshil1712 Check out @sudoingX posts on running llama cpp flags (mostly around nvidia 3090 GPU) and @UnslothAI docs on running harnesses like Claude code locally.
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Harshil
Harshil@harshil1712·
Last night I tried deploying a model to a GPU. The model I was planning to deploy is 120 GB+ and of course my mac can't handle it. Looking for a smaller model now
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andyg5000
andyg5000@AndyG5000·
@sudoingX Just got a 3090 last week so your timing with all this testing and posts has been fantastic. Thank you!
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Sudo su
Sudo su@sudoingX·
if you have a single RTX 3090 and want the best local inference setup right now, here's what i landed on after testing 5 open source models across 7 GPU configs this month. GPU: 1x RTX 3090 24GB model: Qwen 3.5 27B Dense Q4_K_M (16.7GB) context: 262K (native max) speed: 35 tok/s generation, flat from 4K to 300K+ reasoning: built in chain of thought, survives Q4 quant config: llama-server -ngl 99 -c 262144 -fa on --cache-type-k q4_0 --cache-type-v q4_0 what this gives you: - 27B params all active every token - no speed degradation as context fills - full reasoning mode on a consumer GPU - 7GB VRAM headroom after model load tested MoE (faster but less depth per token) and dense hermes (same speed, degraded under load). qwen dense hit the sweet spot for single GPU. more architecture comparisons dropping soon. what's your single GPU setup? curious what configs people are running.
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andyg5000
andyg5000@AndyG5000·
@sudoingX Realized 124 tok/s was at 4K context, not 262K. vLLM eats most of the 24GB leaving almost nothing for KV cache. Apologies for the goose chase! --max-model-len 4096 --gpu-memory-utilization 0.92 --max-num-seqs 2 --kv-cache-dtype fp8 --enable-prefix-caching --language-model-only
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andyg5000
andyg5000@AndyG5000·
@sudoingX replicated on vLLM. RTX 3090, Qwen3.5-35B-A3B AWQ 4-bit. 124 tok/s. key flags: --kv-cache-dtype fp8, --enable-prefix-caching, --no-enforce-eager (CUDA graphs), --language-model-only Beating the 112 tok/s llama.cpp number with batched serving ready out of the box!
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thedroptimes
thedroptimes@thedroptimes·
Carlos Ospina @camoa proposes a blueprint for sub-$2,000 Drupal projects in emerging markets. Leveraging Drupal CMS 2.0, Recipes, Canvas, and supervised AI workflows, he argues standardisation can reduce build time without losing scalability. Details: bit.ly/4cOnxzX
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thedroptimes
thedroptimes@thedroptimes·
Carlos Ospina @camoa releases structured Claude-based tools for Drupal devs and designers. New features include plugin architecture support, a brand content generator, and QA auditing via DDEV. Explore his open-source Claude Skills repo: bit.ly/3YAYSXb
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