Thank you! That gives me a starting point that should be easy to look up!

Why is 255 off limits? What is 127.0.0.0 used for?

To clarify, I meant that specific address - if the range starts at 127.0.0.1 for local, then surely 127.0.0.0 does something (or is reserved to sometimes do something, even if it never actually does in practice), too.

Advanced setup would include a reverse proxy to forward the requests from the applications port to the internet

I use Traefik as my reverse proxy, but I have everything on subdomains for simplicity’s sake (no path mapping except when necessary, which it generally isn’t). I know 127.0.0.53 has special meaning when it comes to how the machine directs particular requests, but I never thought to look into whether Traefik or any other reverse proxy supported routing rules based on the IP address. But unless there’s some way to specify that IP and the IP of the machine, it would be limited to same device communications. Makes me wonder if that’s used for any container system (vs the use of the 10, 172.16-31, and 192.168 blocks that I’ve seen used by Docker).

Well this is another advanced setup but if you wanted to segregate two application on different subnets you can. I’m not sure if there is a security benefit by adding the extra hop

Is there an extra hop when you’re still on the same machine? Like an extra resolution step?

I still don’t understand why .255 specifically is prohibited. 8 bits can go up to 255, so it seems weird to prohibit one specific value. I’ve seen router subnet configurations that explicitly cap the top of the range at .254, though - I feel like I’ve also seen some that capped at .255 but I don’t have that hardware available to check. So my assumption is that it’s implementation specific, but I can’t think of an implementation that would need to reserve all the .255 values. If it was just the last one, that would make sense - e.g., as a convention for where the DHCP server lives on each network.

Why is 255 off limits? What is 127.0.0.0 used for?

I thought Hue bulbs used Zigbee?

The up arrow moves through the letters, e.g., A->B->C. The down arrow moves to the next character in the sequence, e.g., C->CA->CAA. If you click past the correct letter, you’ll have to click all the way through again. And if you submit the wrong letter, you have to start all over (after it takes twenty seconds attempting to connect with the wrong password and then alerts you that it didn’t work, of course).

What a misleading, clickbait title:

Mozilla moves away from open source

When the author really meant:

Mozilla does a thing I don’t like

OP is also in the allegedly ultra rare camp of “successfully configured Jellyfin and lived to tell the tale.” Not what I’d expect of someone unable to configure Plex correctly. I’ve not set up a Plex server myself but my guess is it wasn’t clear that it was misconfigured - it did work previously, after all.

If they’re calling it remote streaming when you’re on the same (local) network, that’s not exactly intuitive. I’d say OP’s phrasing was fair.

Is your goal to create things that can be published or used in a project, or to create audiobooks for yourself to listen to?

For voiceovers for text, I use Kokoro Fast API, which has a web frontend. The frontend is only compatible with Chromium browsers on desktop or Android, which sucks as my daily driver is Firefox and an iPhone (there are workarounds in the thread) but it supports voice mixing, speed changes, etc… It also has an issue where it keeps the models (about 3GB) in memory; I keep the CPU version loaded normally and swap to the GPU version if I need it to be faster. If you want something similar for Bark, check out Bark-GUI.

I’ve also dabbled a bit in some TTS features that have Comfy nodes, though at this point mostly just in terms of getting them set up. For my purposes thus far Kokoro has been fine (and I prefer the FastAPI project over the Comfy nodes for most of my uses), but I’ve found nodes for Kokoro, Dia, F5 TTS, Orpheus, and Zonos.

Autiobooks and audiblez both look promising. A few weeks ago, I used the Kokoro FastAPI web frontend to create an audiobook for an ebook I worked on that used entirely self-hosted AI generation for the outlining and prose. Audiblez, which I found about like two days after that, looks like it would have simplified that process substantially. Still, I’d personally like something more like an audiobook studio, where I can more easily swap voices back and forth, add emotions, play with speed on a more granular level, etc… I’m thinking about building something that contains that at some point myself, but it’ll be a minute - hopefully someone else will beat me there.

I posted a comment here a few weeks back on a similar topic. I’ve since used OpenReader-WebUI and like it, though that’s not for producing audiobooks, but for a read-along experience. Reproducing the comment below in case it’s helpful for you:

If you want to generate audiobooks using your own / a hosted TTS server, check out one of these options:

• OpenReader-WebUI - this has built-in read along capability and can be deployed as a PWA that can allow you to download the audiobooks to your phone so you can use them offline
• p0n1/epub to audiobook
• ebook2audiobook If you don’t have a decent GPU, Kokoro is a great option as it’s fast enough to run on CPU and still sounds very good. If you’re going to use Kokoro, Audiblez (posted by another commenter) looks like it makes that more of an all-in-one option. If you want something that you can use without an upfront building of the audiobook, of the above options, only OpenReader-WebUI supports that. RealtimeTTS is a library that handles that, but I don’t know if there are already any apps out there that integrate it. If you have the audiobook generation handled and just want to be able to follow along with text / switch between text and audio, check out https://storyteller-platform.gitlab.io/storyteller/

The one I grabbed to test was the ROG Azoth.

I also checked my Iris and Moonlander - both cap out at 6, but I believe I can update that to be higher with QMK or add a config key via Oryx on the Moonlander to turn it on.

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Per this thread from 2009, the limit was conditional upon using a particular keyboard descriptor documented elsewhere in the spec, but keyboards are not required to use that descriptor.

I tested just now on one of my mechanical keyboards, on MacOS, connected via USB C, using the Online Key Rollover Test, and was able to get 44 keys registered at the same time.

You can run a NAS with any Linux distro - your limiting factor is having enough drive storage. You might want to consider something that’s great at using virtual machines (e.g., Proxmox) if you don’t like Docker, but I have almost everything I want running in Docker and haven’t needed to spin up a single virtual machine.

Copied from the post:

You may have seen reports of leaks of older text messages that had previously been sent to Steam customers. We have examined the leak sample and have determined this was NOT a breach of Steam systems.​

​

We’re still digging into the source of the leak, which is compounded by the fact that any SMS messages are unencrypted in transit, and routed through multiple providers on the way to your phone.​

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The leak consisted of older text messages that included one-time codes that were only valid for 15-minute time frames and the phone numbers they were sent to. The leaked data did not associate the phone numbers with a Steam account, password information, payment information or other personal data. Old text messages cannot be used to breach the security of your Steam account, and whenever a code is used to change your Steam email or password using SMS, you will receive a confirmation via email and/or Steam secure messages.​

​

You do not need to change your passwords or phone numbers as a result of this event. It is a good reminder to treat any account security messages that you have not explicitly requested as suspicious. We recommend regularly checking your Steam account security at any time at ​

https://store.steampowered.com/account/authorizeddevices​

​

We also recommend setting up the Steam Mobile Authenticator if you haven’t already, as it gives us the best way to send secure messages about your account and your account’s safety.

I’d just like to interject for a moment. What you’re referring to as Alpine Linux Alpine Linux is in fact Pine’s fork, Alpine / Alpine Linux Pine Linux, or as I’ve taken to calling it, Pine’s Alpine plus Alpine Linux Pine Linux. Alpine Linux Pine Linux is an operating system unto itself, and Pine’s Alpine fork is another free component of a fully functioning Alpine Linux Pine Linux system.

Wow, there isn’t a single solution in here with the obvious answer?

You’ll need a domain name. It doesn’t need to be paid - you can use DuckDNS. Note that whoever hosts your DNS needs to support dynamic DNS. I use Cloudflare for this for free (not their other services) even though I bought my domains from Namecheap.

Then, you can either set up Let’s Encrypt on device and have it generate certs in a location Jellyfin knows about (not sure what this entails exactly, as I don’t use this approach) or you can do what I do:

1. Set up a reverse proxy - I use Traefik but there are a few other solid options - and configure it to use Let’s Encrypt and your domain name.
2. Your reverse proxy should have ports 443 and 80 exposed, but should upgrade http requests to https.
3. Add Jellyfin as a service and route in your reverse proxy’s config.

On your router, forward port 443 to the outbound secure port from your PI (which for simplicity’s sake should also be port 443). You likely also need to forward port 80 in order to verify Let’s Encrypt.

If you want to use Jellyfin while on your network and your router doesn’t support NAT loopback requests, then you can use the server’s IP address and expose Jellyfin’s HTTP ports (e.g., 8080) - just make sure to not forward those ports from the router. You’ll have local unencrypted transfers if you do this, though.

Make sure you have secure passwords in Jellyfin. Note that you are vulnerable to a Jellyfin or Traefik vulnerability if one is found, so make sure to keep your software updated.

If you use Docker, I can share some config info with you on how to set this all up with Traefik, Jellyfin, and a dynamic dns services all up with docker-compose services.

Look up “LLM quantization.” The idea is that each parameter is a number; by default they use 16 bits of precision, but if you scale them into smaller sizes, you use less space and have less precision, but you still have the same parameters. There’s not much quality loss going from 16 bits to 8, but it gets more noticeable as you get lower and lower. (That said, there’s are ternary bit models being trained from scratch that use 1.58 bits per parameter and are allegedly just as good as fp16 models of the same parameter count.)

If you’re using a 4-bit quantization, then you need about half that number in VRAM. Q4_K_M is better than Q4, but also a bit larger. Ollama generally defaults to Q4_K_M. If you can handle a higher quantization, Q6_K is generally best. If you can’t quite fit it, Q5_K_M is generally better than any other option, followed by Q5_K_S.

For example, Llama3.3 70B, which has 70.6 billion parameters, has the following sizes for some of its quantizations:

• q4_K_M (the default): 43 GB
• fp16: 141 GB
• q8: 75 GB
• q6_K: 58 GB
• q5_k_m: 50 GB
• q4: 40 GB
• q3_K_M: 34 GB
• q2_K: 26 GB

This is why I run a lot of Q4_K_M 70B models on two 3090s.

Generally speaking, there’s not a perceptible quality drop going to Q6_K from 8 bit quantization (though I have heard this is less true with MoE models). Below Q6, there’s a bit of a drop between it and 5 and then 4, but the model’s still decent. Below 4-bit quantizations you can generally get better results from a smaller parameter model at a higher quantization.

TheBloke on Huggingface has a lot of GGUF quantization repos, and most, if not all of them, have a blurb about the different quantization types and which are recommended. When Ollama.com doesn’t have a model I want, I’m generally able to find one there.

I recommend a used 3090, as that has 24 GB of VRAM and generally can be found for $800ish or less (at least when I last checked, in February). It’s much cheaper than a 4090 and while admittedly more expensive than the inexpensive 24GB Nvidia Tesla card (the P40?) it also has much better performance and CUDA support.

I have dual 3090s so my performance won’t translate directly to what a single GPU would get, but it’s pretty easy to find stats on 3090 performance.

The above post says it has support for Ollama, so I don’t think this is the case… but the instructions in the Readme do make it seem like it’s dependent on OpenAI.

Are you saying that NAT isn’t effectively a firewall or that a NAT firewall isn’t effectively a firewall?