u/entsnack

Been almost a year since mass hysteria erupted upon the death of NVIDIAs GPU monopoly. How are your Huawei GPUs? Does CUDA work on them yet?

Timestamps: https://imgur.com/a/DHy8A8C

$100 shipped! Comes with the stock cooler and box. Fits LGA 1700 mobos, no integrated graphics.

I've set up slsdkd on my Raspberry Pi headless server. Something I often do is check if an album is a vinyl rip (I HATE the noise and clicks) by downloading a song and inspecting it using ffmpeg. Turns out this is a really good task for a coding agent like Codex (which also works really well to set up a song download when you're on the go). You do need to nudge GPT into doing what you want though (tip in the video).

This is in response to the common post where OP has acquired some cool hardware and is wondering what to do with it. The standard response is always (1) download model X, (2) benchmark it on tps, (3) share screenshots. I argue this is boring and intellectually lazy, and propose an alternative: post-training.

For background: I have been "post-training-as-a-service" for 4 years now. I started out with simply SFTing (supervised fine-tuning) BERT-style models for my clients' tasks on a 4090 server. These are not chat use cases, they're for things like (a) identifying if a chat is a malicious consumer trying to get a refund, (b) tagging a sequence of mouse movements and keypresses for potential corporate espionage, (c) helping salespeople profile consumer traits and needs in real-time. These are all real project by the way, that I earned quite a lot from (and continue to do so today).

Unlike what inference monkeys do, post-training is non-trivial. For starters, quality and speed both matter; you're not going to get away with a false positive rate of 80% at 1,000 tokens per second. In fact, the TPS is not very important because a lot of post-training use cases are not real-time (though some of them are). Second, post-training recipes are a dark art: you will not find tutorials or guides, Claude/Codex cannot vibe it for you (I've tried), and it's still incredibly in demand (check out this recent paper to get a sense of how much of a dark art it is). Third, the data mix is key: your client will give you some data, you will ask for more, eventually you'll need to do some clever data synthesis and transformation to unlock performance. Fourth, different data + model combinations perform differently. The Qwens for example are difficult to post-train, they're crammed with knowledge (i.e., benchmaxxxed). The stupid Llamas are amazing to post-train, they absorb knowledge because they have so little (but the lack of base knowledge is also bad). Fifth, the faster you can iterate, the faster you can find the best post-trained model and deliver results. This is where engineering and deployment skill comes in: if you understand and purchase the right hardware, you can set up a low-power massively-parallel post-training stack that lets you iterate at speed (hint in the picture).

This is just SFT, the next level is RFT: reinforcement fine-tuning. This is a different ballgame and is the wild west right now. In RFT, you need a model doing inference/rollouts quickly (ideally on a fast token generation machine), that is then given a reward (this may involve spawning Docker containers to build and test code), and finally its weights are updated using PPO/GRPO/RLOO/whatever-it-is-nowadays. It's a cool mix of inference and weight-updates that require a special build-out, and no one knows what the ideal build-out is. Post-training shops like Prime RL run in datacenters, AFAIK no one is doing this solo yet (I am only starting to).

Overall, I hope this post unlocks an interesting new journey for your new hardware. This is all only possible thanks to local LLMs. OpenAI is shutting down its SFT API, and its RFT API is obscenely expensive. So custom post-trains are one of the few projects that are completely in the realm of open models. I see a good opportunity to make money, though a bit competitive and hardware dependent. Enjoy!

Written with zero LLM-assistance, please excuse typos and rambling.

Don't be me. My plan was to swap out my bigass 3.5-slot 4090 and sell it while using the smallass 2-slot blower 4090 for both gaming and AI research. Turns out I cannot stand the fan noise, even with IEMs on. The electronic interference is also significantly higher than consumer cards, I had to switch to bluetooth audio because I couldn't get rid of the buzz. It's an excellent card though (Manli), runs cool and exhausts out the back of my case so my other components stay cool too.

I bought Notability back when it was a $10 one-time purchase. Paired with a nice terminal app like rootshell, it makes the iPad the perfect device to implement math-heavy algorithms (here I am implementing a bandit from Sutton and Barto). Anyone else have a touch/type workflow?

I recently purchased the Huginn: a concept streamer from the OP of the linked post. This Raspberry Pi 5-based streamer has become the endgame source for my Schiit stack. I thought I'd share a quick review and shoutout to u/FCK_COVID19 for agreeing to sell this to me. For my needs, I much prefer this to pricier alternatives like the $1000 Kitsune HoloAudio Red.

The chassis. Huginn looks and feels similar to a standard Schiit unit. The shell is heavy, dense sheets of metal (likely aluminum or steel) that give it a solid, premium feel. More practically, the weight helps keep Huginn in place when plugging cables in and out. The chassis is perforated on either side, has a small slot at the front bottom (below the logo) for SD card access, a cutout at the top for the passive heatsink, and 4 rubber feet.

Interestingly, a momentary toggle switch protrudes from the back and triggers power using the Pi 5's J2 jumper. Some very clever engineering holds the switch in place when triggered. The toggle is longer than the usual Schiit switch.

The rear has cutouts for the Waveshare Pi 5 connector's ports along with the Raspberry Pi 5's USB type A and ethernet port. I would have liked a small shield to cover all of these up and expose just the USB-C port, because that's really all you need with this device. In my setup, a Belkin USB-C power + data splitter is plugged in to the Pi 5's USB-C port, sending bitperfect audio out to my Modi and consuming power from the Pi 5 27W wall adapter (a standard 15W adapter works too, but the risk of brownouts is higher).

The chassis internals are incredibly engineered. To deal with the limited space for a Raspberry Pi 5, the switch circuit, the custom passive heatsink, and an NVME SSD, the Huginn arranges components in 3 layers. At the bottom is the Pi 5 + Waveshare connector board and the switch circuit. Above that, on standoffs fastened to the chassis through the Pi 5's mounting holes, is the custom heatsink. And finally, the NVME adapter and drive are mounted above that on a separate triplet of standoffs.

A note on assembly. If you've ever worked on a German car, you'll be familiar with the joys of assembling and disassembling components in a strict order with limited space for tools and your hands. This unit took me about 2 hours to assemble, and may require some soldering (particularly for the switch to the Pi 5 J2 holes). Rev 2.0 of the Waveshare Pi 5 connector has a screw terminal which the chassis does not support; I removed it by carefully pulling the housing out with a pair of pliers. Apart from those 2 aspects, assembly is straightforward if you're slow and careful.

Software. I run moOde on a 1 GB Raspberry Pi 5 (the Pi 4 is not compatible with this chassis). moOde does a great job configuring the Linux distribution to not write to the SD card (and risk corruption) and use ALSA (for bitperfect USB audio output).

Instead of using the built-in moOde client, I use rmpc inside rootshell on my iPad, and MPD Pilot on my phone. You could use Plexamp headless and the Plexamp apps instead, but you won't get automatic sample rate matching unless you pay a monthly fee (which makes no sense).

My music is stored on an old iMac 5K (which also runs Plex, Soulseek, and syncs to my iPod) and NFS-mounted on the Pi 5. I don't use an NVME SSD yet.

Pi 5 FAQs. The Pi 5 stays cool, never exceeding 45 C even playing 24/192 FLACs. RAM usage hovers around 600 MB. This is not surprising, because all this is doing is transferring bits from one source to another.

If you happen to do something computationally heavy while playing 24/192 music (e.g., compiling code), music playback will stutter until the CPU load subsides. This is likely a problem with me using the USB-C port for audio out. The USB otg scheduler is not as good as the one that powers the USB type A ports. So if you plan to do things on the Pi 5 while playing music, you will be better served adding a USB type A to type C cable to send audio to the DAC.

Summary. I'm smitten by this device. Try to snag version 2.0 of Huginn from u/FCK_COVID19, not sure whether and how long he's going to keep making these.

I recently purchased the Huginn: a concept streamer from the OP of the linked post. This Raspberry Pi 5-based streamer has become the endgame source for my Schiit stack. I thought I'd share a quick review and shoutout to u/FCK_COVID19 for agreeing to sell this to me. For my needs, I much prefer this to pricier alternatives like the $1000 Kitsune HoloAudio Red.

The chassis. Huginn looks and feels similar to a standard Schiit unit. The shell is heavy, dense sheets of metal (likely aluminum or steel) that give it a solid, premium feel. More practically, the weight helps keep Huginn in place when plugging cables in and out. The chassis is perforated on either side, has a small slot at the front bottom (below the logo) for SD card access, a cutout at the top for the passive heatsink, and 4 rubber feet.

Interestingly, a momentary toggle switch protrudes from the back and triggers power using the Pi 5's J2 jumper. Some very clever engineering holds the switch in place when triggered. The toggle is longer than the usual Schiit switch.

The rear has cutouts for the Waveshare Pi 5 connector's ports along with the Raspberry Pi 5's USB type A and ethernet port. I would have liked a small shield to cover all of these up and expose just the USB-C port, because that's really all you need with this device. In my setup, a Belkin USB-C power + data splitter is plugged in to the Pi 5's USB-C port, sending bitperfect audio out to my Modi and consuming power from the Pi 5 27W wall adapter (a standard 15W adapter works too, but the risk of brownouts is higher).

The chassis internals are incredibly engineered. To deal with the limited space for a Raspberry Pi 5, the switch circuit, the custom passive heatsink, and an NVME SSD, the Huginn arranges components in 3 layers. At the bottom is the Pi 5 + Waveshare connector board and the switch circuit. Above that, on standoffs fastened to the chassis through the Pi 5's mounting holes, is the custom heatsink. And finally, the NVME adapter and drive are mounted above that on a separate triplet of standoffs.

A note on assembly. If you've ever worked on a German car, you'll be familiar with the joys of assembling and disassembling components in a strict order with limited space for tools and your hands. This unit took me about 2 hours to assemble, and may require some soldering (particularly for the switch to the Pi 5 J2 holes). Rev 2.0 of the Waveshare Pi 5 connector has a screw terminal which the chassis does not support; I removed it by carefully pulling the housing out with a pair of pliers. Apart from those 2 aspects, assembly is straightforward if you're slow and careful.

Software. I run moOde on a 1 GB Raspberry Pi 5 (the Pi 4 is not compatible with this chassis). moOde does a great job configuring the Linux distribution to not write to the SD card (and risk corruption) and use ALSA (for bitperfect USB audio output).

Instead of using the built-in moOde client, I use rmpc inside rootshell on my iPad, and MPD Pilot on my phone. You could use Plexamp headless and the Plexamp apps instead, but you won't get automatic sample rate matching unless you pay a monthly fee (which makes no sense).

My music is stored on an old iMac 5K (which also runs Plex, Soulseek, and syncs to my iPod) and NFS-mounted on the Pi 5. I don't use an NVME SSD yet.

Pi 5 FAQs. The Pi 5 stays cool, never exceeding 45 C even playing 24/192 FLACs. RAM usage hovers around 600 MB. This is not surprising, because all this is doing is transferring bits from one source to another.

If you happen to do something computationally heavy while playing 24/192 music (e.g., compiling code), music playback will stutter until the CPU load subsides. This is likely a problem with me using the USB-C port for audio out. The USB otg scheduler is not as good as the one that powers the USB type A ports. So if you plan to do things on the Pi 5 while playing music, you will be better served adding a USB type A to type C cable to send audio to the DAC.

Summary. I'm smitten by this device. Try to snag version 2.0 of Huginn from u/FCK_COVID19, not sure whether and how long he's going to keep making these.

I recently purchased the Huginn: a concept streamer from the OP of the linked post. This Raspberry Pi 5-based streamer has become the endgame source for my Schiit stack. I thought I'd share a quick review and shoutout to u/FCK_COVID19 for agreeing to sell this to me. For my needs, I much prefer this to pricier alternatives like the $1000 Kitsune HoloAudio Red.

The chassis. Huginn looks and feels similar to a standard Schiit unit. The shell is heavy, dense sheets of metal (likely aluminum or steel) that give it a solid, premium feel. More practically, the weight helps keep Huginn in place when plugging cables in and out. The chassis is perforated on either side, has a small slot at the front bottom (below the logo) for SD card access, a cutout at the top for the passive heatsink, and 4 rubber feet.

Interestingly, a momentary toggle switch protrudes from the back and triggers power using the Pi 5's J2 jumper. Some very clever engineering holds the switch in place when triggered. The toggle is longer than the usual Schiit switch.

The rear has cutouts for the Waveshare Pi 5 connector's ports along with the Raspberry Pi 5's USB type A and ethernet port. I would have liked a small shield to cover all of these up and expose just the USB-C port, because that's really all you need with this device. In my setup, a Belkin USB-C power + data splitter is plugged in to the Pi 5's USB-C port, sending bitperfect audio out to my Modi and consuming power from the Pi 5 27W wall adapter (a standard 15W adapter works too, but the risk of brownouts is higher).

The chassis internals are incredibly engineered. To deal with the limited space for a Raspberry Pi 5, the switch circuit, the custom passive heatsink, and an NVME SSD, the Huginn arranges components in 3 layers. At the bottom is the Pi 5 + Waveshare connector board and the switch circuit. Above that, on standoffs fastened to the chassis through the Pi 5's mounting holes, is the custom heatsink. And finally, the NVME adapter and drive are mounted above that on a separate triplet of standoffs.

A note on assembly. If you've ever worked on a German car, you'll be familiar with the joys of assembling and disassembling components in a strict order with limited space for tools and your hands. This unit took me about 2 hours to assemble, and may require some soldering (particularly for the switch to the Pi 5 J2 holes). Rev 2.0 of the Waveshare Pi 5 connector has a screw terminal which the chassis does not support; I removed it by carefully pulling the housing out with a pair of pliers. Apart from those 2 aspects, assembly is straightforward if you're slow and careful.

Software. I run moOde on a 1 GB Raspberry Pi 5 (the Pi 4 is not compatible with this chassis). moOde does a great job configuring the Linux distribution to not write to the SD card (and risk corruption) and use ALSA (for bitperfect USB audio output).

Instead of using the built-in moOde client, I use rmpc inside rootshell on my iPad, and MPD Pilot on my phone. You could use Plexamp headless and the Plexamp apps instead, but you won't get automatic sample rate matching unless you pay a monthly fee (which makes no sense).

My music is stored on an old iMac 5K (which also runs Plex, Soulseek, and syncs to my iPod) and NFS-mounted on the Pi 5. I don't use an NVME SSD yet.

Pi 5 FAQs. The Pi 5 stays cool, never exceeding 45 C even playing 24/192 FLACs. RAM usage hovers around 600 MB. This is not surprising, because all this is doing is transferring bits from one source to another.

If you happen to do something computationally heavy while playing 24/192 music (e.g., compiling code), music playback will stutter until the CPU load subsides. This is likely a problem with me using the USB-C port for audio out. The USB otg scheduler is not as good as the one that powers the USB type A ports. So if you plan to do things on the Pi 5 while playing music, you will be better served adding a USB type A to type C cable to send audio to the DAC.

Summary. I'm smitten by this device. Try to snag version 2.0 of Huginn from u/FCK_COVID19, not sure whether and how long he's going to keep making these.

I recently set up a Raspberry Pi 5 as a headless streamer with moOde and was looking for a nice iOS client. Turns out running rmpc in the rootshell terminal app does the trick and looks great too with the Kitty-powered album art! The only other worthwile iOS client I found was MPD Pilot, but it's not infinitely configurable like rmpc. Still need to find a way to show lyrics synced with time.

Pictures and video with timestamps: [https://imgur.com/a/l9t5Sby\](https://imgur.com/a/l9t5Sby)

$2300 local cash, local is upstate NY but can drive some distance. I'll be in NYC today if anyone wants to make a quick sale.

Includes original box and all accessories: stock 12VHPWR cable (unused), mounting bracket (2 pieces), motherboard standoff screws (4) and fasteners. Ports are protected with dust plugs. Used for VR gaming and Street Fighter 6 in a smoke free home.

I just cancelled my music subscriptions to save some cash and wanted to share the self-hosted music supply chain that replaced them. A nice side effect of this setup is breaking the constraint of a finite supply catalog that is tailored for the masses:

0. 2 x DGX Spark linked via ConnectX 7 running Plex and multiple Ace-Step 1.5 XL models in parallel for music generation with GePa prompt optimization. Also holds my organic music that the models can remix. TODO: a reinforcement learning from human feedback interface.

1. iPad Pro running Prism as a Plex client for bitperfect and sample rate-matched audio.

2. Schiit stack -> Hifiman Arya Stealths

This effectively gives me an infinite supply of music for free, that is personalized and private. It's immensely satisfying listening to Shrimp Bizkit and Phlegminem on repeat, I much prefer this to the organic music created after 2011.

My only problem is the loss of community, I have noone to share my new favorite songs and artists with because they're generated for me. If anyone wants to hop on to my Plex share to discuss, let me know!

I just cancelled my music subscriptions to save some cash and wanted to share the self-hosted music supply chain that replaced them. A nice side effect of this setup is breaking the constraint of a finite supply catalog that is tailored for the masses:

0. 2 x DGX Spark linked via ConnectX 7 running Plex and multiple Ace-Step 1.5 XL models in parallel for music generation with GePa prompt optimization. Also holds my organic music that the models can remix. TODO: a reinforcement learning from human feedback interface.

1. iPad Pro running Prism as a Plex client for bitperfect and sample rate-matched audio.

2. Schiit stack -> Hifiman Arya Stealths

This effectively gives me an infinite supply of music for free, that is personalized and private. It's immensely satisfying listening to Shrimp Bizkit and Phlegminem on repeat (my own artist names), I much prefer this to the organic music created after 2011.

My only problem is the loss of community, I have noone to share my new favorite songs and artists with because they're generated for me. If anyone wants to hop on to my Plex share to discuss, let me know!

Timestamped pics

Selling my barely-used Pi 4B 4GB to fund a Pi 5. $75 incl. CONUS shipping.