Ahh yes, the window that is worth more than my life.
This is why you hardwire the dashcam.
That is National Fisheries Development Board in Hyderabad, India.
I assumed that they might be referring to either pets or kids in her class at school. Don't teachers have to pay for stuff out of pocket a lot of times?
The fuck does no real bills mean? Does eating, rent and gas/insurance not count as real bill?
Or the ever classic: launch one version behind the current Android version. Provide security update once a year and then taut that it's aon OS update.
That's true of any politician tbh, I'm indian and most of the elections are about how we were great and ancient and holy and blah blah.
Samsung A9+ goes on sale for about $150 every once in a while.
Kids FireHD tablets are generally lower than that. There's not really any difference between the adult and kids version tbh.
Why do people sleep on KDE connect? It does a lot of things really well and is OS agnostic.
Does this support Android Auto? That's the only reason I use maps.
Dang, you're Moneyball'ing your kid?
Sounds awesome!
Windows laptops generally get trashy battery life, and if this going to tank it further, I'd just run Linux full-time on my family laptop and call it a day.
The only reason we had windows was my wife's comfortability and sometimes zoom glitches out on linux.
You can import a whole bunch of stuff, but it's upto each state to decide if they'll allow you to use it on road.
Oh absolutely. I wear socks with sandals because my soles sweat and make my sandals sticky.
But yeah, wear proper attire for the work you do!
Absolutely, my toddler had MRSA within a few days after he was born and its most likely due to some contamination or something to the effect.
Hospitals are a severe breeding grounds for resistant bacterial strains via sewage.
Absolutely. My wife flew to her parent place with our toddler and I dont have any idea on what to watch.
All I'm watching is nursery rhymes since they're catchy as all hell.
Resonate this super hard, and I'm in the second camp.
Everything seems to set me off at home. I just want to rage against everyone and it's fucking shameful.
ThinkPad T450s (my old laptop)
OS: Arch Linux DE: Plasma
Services: Arr stack for gluetun, sonarr, radar and jackets Jellyfin for videos Gonic for audio
All 3 of them are run using docker compose
This has the same energy as my spouse yelling at me because jellyfin went down
Hi!
I have an ASUS AMD Advantage Edition laptop (https://rog.asus.com/laptops/rog-strix/2021-rog-strix-g15-advantage-edition-series/) that runs windows. I haven't gotten time to install linux and set it up the way I like yet, still after more than a year.
I'm just dropping a small write-up for the set-up that I'm using with llama.cpp to run on the discrete GPUs using clbast.
You can use Kobold but it meant for more role-playing stuff and I wasn't really interested in that. Funny thing is Kobold can be set up to use the discrete GPU if needed.
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For starters you'd need llama.cpp itself from here: https://github.com/ggerganov/llama.cpp/tags.
Pick the clblast version, which will help offload some computation over to the GPU. Unzip the download to a directory. I unzipped it to a folder called this: "D:\Apps\llama\"
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You'd need a llm now and that can be obtained from HuggingFace or where-ever you'd like it from. Just note that it should be in ggml format. If you have a doubt, just note that the models from HuggingFace would have "ggml" written somewhere in the filename. The ones I downloaded were "nous-hermes-llama2-13b.ggmlv3.q4_1.bin" and "Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_0.bin"
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Move the models to the llama directory you made above. That makes life much easier.
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You don't really need to navigate to the directory using Explorer. Just open Powershell where-ever and you can also do cd D:\Apps\llama\
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Here comes the fiddly part. You need to get the device ids for the GPU. An easy way to check this is to use "GPU caps viewer", go to the tab titled OpenCl and check the dropdown next to "No. of CL devices".
The discrete GPU is normally loaded as the second or after the integrated GPU. In my case the integrated GPU was gfx90c and discrete was gfx1031c.
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In the powershell window, you need to set the relevant variables that tell llama.cpp what opencl platform and devices to use. If you're using AMD driver package, opencl is already installed, so you needn't uninstall or reinstall drivers and stuff.
$env:GGML_OPENCL_PLATFORM = "AMD"
$env:GGML_OPENCL_DEVICE = "1"
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Check if the variables are exported properly
Get-ChildItem env:GGML_OPENCL_PLATFORM Get-ChildItem env:GGML_OPENCL_DEVICE
This should return the following:
Name Value
---- -----
GGML_OPENCL_PLATFORM AMD
GGML_OPENCL_DEVICE 1
If GGML_OPENCL_PLATFORM doesn't show AMD, try exporting this: $env:GGML_OPENCL_PLATFORM = "AMD"
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Once these are set properly, run llama.cpp using the following:
D:\Apps\llama\main.exe -m D:\Apps\llama\Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_0.bin -ngl 33 -i --threads 8 --interactive-first -r "### Human:"
OR
replace Wizard with nous-hermes-llama2-13b.ggmlv3.q4_1.bin or whatever llm you'd like. I like to play with 7B, 13B with 4_0 or 5_0 quantized llms. You might need to trawl through the fora here to find parameters for temperature, etc that work for you.
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Checking if these work, I've posted the content at pastebin since formatting these was a paaaain: https://pastebin.com/peSFyF6H
salient features @ gfx1031c (6800M discrete graphics): llama_print_timings: load time = 60188.90 ms llama_print_timings: sample time = 3.58 ms / 103 runs ( 0.03 ms per token, 28770.95 tokens per second) llama_print_timings: prompt eval time = 7133.18 ms / 43 tokens ( 165.89 ms per token, 6.03 tokens per second) llama_print_timings: eval time = 13003.63 ms / 102 runs ( 127.49 ms per token, 7.84 tokens per second) llama_print_timings: total time = 622870.10 ms
salient features @ gfx90c (cezanne architecture integrated graphics): llama_print_timings: load time = 26205.90 ms llama_print_timings: sample time = 6.34 ms / 103 runs ( 0.06 ms per token, 16235.81 tokens per second) llama_print_timings: prompt eval time = 29234.08 ms / 43 tokens ( 679.86 ms per token, 1.47 tokens per second) llama_print_timings: eval time = 118847.32 ms / 102 runs ( 1165.17 ms per token, 0.86 tokens per second) llama_print_timings: total time = 159929.10 ms
Edit: added pastebin since I actually forgot to link it. https://pastebin.com/peSFyF6H