netrunner @plotarmordev
Cofounder & engineer. Running local AI, building things with it, and sharing what I learn. Joined April 2022-
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@CryptoBandit100 @NVIDIAAI @MiaAI_lab @ashxhart 🙏 lmk how it goes
NEW: Nemotron 3.5 Super VL was looking at every image twice. Now it looks once, so replies start 28% sooner on a single DGX Spark, with the same answers! The fix is on its way into TensorFold. If you run Super VL, get it first in the recipe: github.com/plotarmordev/N…
I never thought I'd get into X's creator program. This week I did 🙏 thanks to all of you who read and reply. Since Aug I've been following @MiaAI_lab's playbook "From Zero to Seen", and 10k impressions a day became 50k. Feel invisible? start there mia-ai.net/book
@StevenMatison 35b still leaves a lot of room around it
When I started with my 3 DGX Sparks, 2 were dedicated to running models and 1 handled compute so I could keep working on the go. Now each one runs 2 different models or 2 heavy jobs, and usage is close to 100% with all of them. Anyone else changing how they use their Sparks, or do you prefer to load the biggest model you can fit?
@wikiwayne my coordinator agent decides for me, optimizes for max and efficient usage
Say MiniMax drops the M3.1 Flash weights soon. How it stacks locally comes down to the size. There's no parameter count so far. IF it fits on a single Spark that would be awesome, because it goes straight up against DeepSeek V4.1 Flash, which we run across 2.
Welcome back. Space Bunny. 🚀 MiniMax-M3.1-Flash is coming.
@robertomasymas Still very valid, what kind of trainings are you running?
@ivanfioravanti @NVIDIAAI @MiaAI_lab @ashxhart Thanks Ivan, are you running this model too?
@ashxhart @NVIDIAAI @MiaAI_lab thanks man, glad it's useful 🙏
@MichaelHutu @NVIDIAAI @MiaAI_lab @ashxhart Thanks! You’ll find the improvements on my recipe first then they’ll be all on TensorFold so people building with it can start from the new baselines. The split sounds clean btw! lmk how super vl holds up as the daily driver on #1
@kkiran each model on its own job? Or is it related to your idea pipeline where each have a specific part in it?
@MichaelGannotti @NVIDIAAI @MiaAI_lab @ashxhart Thanks! A lot more coming, not just for Nemotron 🫡
@MiaAI_lab @NVIDIAAI @ashxhart Thank you! Optimizing this because I think it has some potential given how many companies worked on post trained versions of it
@niklaslenz_ai @MiaAI_lab Wow congrats! Following you from the start 🫡
@ItsmeAjayKV @MiniMax_AI I read @MiaAI_lab instead of @MiniMax_AI 😆
Fourth Ablit Recipe now in the same repo Thank you @MiaAI_lab MiaAi_Lab - DeepSeekv4.1Flash-1017-EAQ-EXL3-2.9BPW now abliterated. HP repo: huggingface.co/drowzeys/keys-…
Third Ablit Recipe now in the same repo Thank you @jayleaton LFG!!!>. Jayleaton - DeepSeekV4.1 Flash -1017 - EXL3- 2.8 BPW is now abliterated inside the HF repo... who is next... 100% abliterated + full C.S. capability enabled huggingface.co/drowzeys/keys-…
@upndownsyndrome 100%, once they're all pinned an idle one starts to feel like money sitting on the desk
@lessing_systems That’s smart! What kept me from swapping a lot is the reload time.
Honestly I’m still experimenting. On my “head” spark I’m running my personal cyber and bug testing harness along with a voice model. On my other two I’m now running a decision model (d1) and nemotron super VL. On the side I run many other models for testings and improving things for everyone else. My goal is trying to use them for things I can’t pay with cloud models essentially.
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