Ollama is a highly automated open source wrapper that makes it very easy to run multiple Open weight LLM models either on CPU or GPU.
Its README alone is of great value, serving as a fantastic list of the most popular Open weight LLM models in existence.
Install with:
curl https://ollama.ai/install.sh | shOn P14s it runs on CPU and generates a few tokens per second, which is quite usable for a quick interactive play.
As mentioned at github.com/jmorganca/ollama/blob/0174665d0e7dcdd8c60390ab2dd07155ef84eb3f/docs/faq.md the downloads to under The file:gives a the exact model name and parameters.
/usr/share/ollama/.ollama/models/ and ncdu tells me:--- /usr/share/ollama ----------------------------------
3.6 GiB [###########################] /.ollama
4.0 KiB [ ] .bashrc
4.0 KiB [ ] .profile
4.0 KiB [ ] .bash_logout/usr/share/ollama/.ollama/models/manifests/hf.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF/Q2_KWe can also do it non-interactively with:which gave me:but note that there is a random seed that affects each run by default. ollama-expect is an attempt to make the output deterministic.
/bin/time ollama run llama2 'What is quantum field theory?'0.13user 0.17system 2:06.32elapsed 0%CPU (0avgtext+0avgdata 17280maxresident)k
0inputs+0outputs (0major+2203minor)pagefaults 0swapsSome other quick benchmarks from Amazon EC2 GPU on a g4nd.xlarge instance which had an Nvidia Tesla T4:and on Nvidia A10G in an g5.xlarge instance:
0.07user 0.05system 0:16.91elapsed 0%CPU (0avgtext+0avgdata 16896maxresident)k
0inputs+0outputs (0major+1960minor)pagefaults 0swaps0.03user 0.05system 0:09.59elapsed 0%CPU (0avgtext+0avgdata 17312maxresident)k
8inputs+0outputs (1major+1934minor)pagefaults 0swapsIt tends to babble quite a lot by default, but eventually decides to stop.
However it did not happen on Lenovo ThinkPad P51 (2017) also on Ubuntu 23.10 which had been upgraded several times from God knows what starting point... At first one had X11 (forced by Nvidia drivers) and the other Wayland, but moving to p14s X11 changed nothing.
Both were running GNOME Display Manager.
Same happens with Super + L, but also CLI commands: askubuntu.com/questions/7776/how-do-i-lock-the-desktop-screen-via-command-line
Bibliography:
- askubuntu.com/questions/1242110/after-upgrading-to-ubuntu-20-04-lockscreen-not-working canon
- askubuntu.com/questions/1246622/ubuntu-20-04-unable-to-lock-screen
- askubuntu.com/questions/1245071/cant-lock-screen-with-shortcut-on-ubuntu-20-04-gnome
- askubuntu.com/questions/1248756/super-l-not-working-on-ubuntu-20-04
- 2008-08-18: bitcoin.org registered
- 2008-10-31: first public announcement at www.metzdowd.com/pipermail/cryptography/2008-October/014810.html by satoshi@vistomail.com
- 2009-01-03: Genesis block mined
- 2009-01-11: First block not mined by Satoshi
- 2009-01-12: First Bitcoin transactoin
- 2010-05-18: the first of Laszlo's pizzas at about $0.0045 / BTC
- 2010-07-17: first trade happes on Mt. Gox at $0.04951 / BTC: cryptopotato.com/10-years-ago-first-bitcoin-trade-on-mt-gox-for-0-05-per-btc/
- 2014: OP_RETURN goes live
convert -size 512x512 xc:blue blue.pngConda is like pip, except that it also manages shared library dependencies, including providing prebuilts.
This has made Conda very popular in the deep learning community around 2020, where using Python frontends like PyTorch to configure faster precompiled backends was extremely common.
It also means that it is a full package manager and extremely overbloated and blows up all the time. People should just use Docker instead for that kind of stuff: www.reddit.com/r/learnmachinelearning/comments/kd88p8/comment/keco07k/
You also have to buy a license to use their repos if you are part of a large-enough organization: stackoverflow.com/questions/74762863/are-conda-miniconda-and-anaconda-free-to-use-and-open-source
Term invented by Ciro Santilli, similar to "nuclear blues", and used to describe the feeling that every little shitty job you are doing (that does not considerably help achieving AGI) is completely pointless given that we are likely close to AGI as of 2023.
en.bitcoin.it/wiki/Jercos mentions:www.bitcoinwhoswho.com/jercosinterview is the source. Persumably the contact was initiated via the private messaging feature of the Bitcoin Forum.
According to jercos the transaction was finalized over IRC chats. Jercos was 18 at the time of the transaction.
Bibliography:
en.bitcoin.it/wiki/Jercos
en.bitcoin.it/wiki/Jercos
There are unlisted articles, also show them or only show them.