Haha. Well, I guess I have a ulterior motive for promoting i2p; the more people get in it and contribute to the network (port forward the NTCP2 and SSU2 to accept transit tunnels) the better network speeds will get! Just the act of torrenting through i2p will help the network tremendously.
I have noticed that speeds in i2pd (c++) are faster than in the original java implementation so maybe you can try that out? It's fast enough for my use case, but yes streaming torrents in i2p is still far away.
But the upside is, you don't have to rely on a VPN to protect yourself against copyright trolls! Plus, putting it on a fully automated *arr stack means you can just add a movie on radarr and let the *arrs take care of everything in about a day or so. I average at about 200-300 KiB / s per well-seeded movie file, and around half that for something poorly seeded.
I haven't tried the i2p docker image, but it shouldd work. Let me know
There are some German and French content that I see occasionally in Postman. In the actual i2p postman site you can filter for the French and German language.
If you're using the docker image the network_mode is set to host, so it should work the same as if i2p was installed without containerization.
where 7656 is the SAM bridge port. I'm using version 4.6.3 of qbittorrent and it has this feature. The arch package for qbittorrent-nox (the webui edition of qbittorrent) already has this feature. I just checked; the latest docker image for qbittorrent should already have this feature! https://github.com/linuxserver/docker-qbittorrent
Not too sure about private trackers. Although, due to the fundamental anonymizing feature of i2p there would be no way for copyright trolls to track IP addresses and send mass lawsuits, which private trackers defend against.
It's all free and open source! If you're on windows it might be a little more difficult so at least having a linux PC you can reliably have on 24/7 would make things easier. I personally use arch (I've tried this on my endeavour OS), very easy installation for beginners) for this since it's rolling release (latest versions of packages!) and the AUR is a godsend. The programs themselves take little ram and cpu, with qbittorrent probably needing the most ram once you have more torrents downloaded (I'm running this on 4 cores of CPU and 4 gigs of ram alongside my minecraft server, a tor relay and a monero node. any old laptop repurposed with endeavour should do the trick)
the steps I took to do this (on endeavour os) was:
install i2pd
sudo pacman -S i2pd
Install qbittorrent webui
sudo pacman -S qbittorrent-nox
install prowlarr (optionally sonarr and radarr, which will automatically manage video files for you. Plays reaaaally well with Jellyfin, so you wouldn't have weirdly formatted files that is being read by Jellyfin)
yay -S prowlarr
yay -S sonarr
yay -S radarr
Lastly you have to turn enable the *arrs in systemd
sudo systemctl enable --now prowlarr
(do the same with sonarr and radarr if you have them)
(or you can also go the docker route with qbittorrent, prowlarr, sonarr and radarr, if you don't have arch. This is the more universal route and can handle many more devices. Although I have not checked if qbittorrent-docker has i2p integration yet. For that you may need to swap out qbittorrent for vuze, or apply the patch in the comment in the link i posted in the docker container [which is editing the qBittorrent.conf file])
For the average joe i'd say it'll be an afternoon's worth of labor to set up, and the upside is not relying on a VPN to install content and a fully automated Jellyfin server! Plus you get to help the steadily-growing i2p network If you have more questions I'd be happy to answer here :)
So it creates a function, a, which what it does is it calls itself and pipes its output to itself (the a | a). The ampersand means that this will run entirely in the background. Then, to initiate things, the command calls a (in the last line)
So, there will be exponentially be many recursive calls to a, which will eventually deplete your stack and set your pc on fire
Hope that open source LLMs take off more than closed source proprietary ones.
data in lemmy is fundamentally open for scraping. Scraping itself isn’t fundamentally bad, but it depends where we feed our data to. I am at ease with my data being used to train an open source LLM (open dataset, open algorithm, open training procedure, etc) rather than used to train microsoft Bing’s new chatbot. At lease we need an open source LLM to be able to compete with the GPTs.
Unrelated question. What’s a video card that can transcode AV1? I want to add more AV1s to my jellyfin server but i’d need at least a nvidia RTX 4060 if i want AV1 transcoding >_<
I’ve only ever self-hosted SearxNG but i wanna try out LibreY. As for who gets rate-linited less, if you self host for yourself plus some friends i’d be surprised if you have Google rate limiting your searches. I didn’t run a problem with mine anyways. I like the “torrents” feature of LibreY tho. I might self host and report back.
The irs will come after you…