(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
Service Worker - offline support for the web
Progressive apps - high-res icon, splash screen, no URL bar, etc.
http://blog.pluralsight.com/elixir-is-for-programmers #Idea assert, test http://www.q-lang.io/ #Definicion tipos como campos DB http://dlang.org/exception-safe.html #Alternativa try--except con scope http://floodyberry.com/noncryptohashzoo/ #Implementaciones de funcion HASH https://github.com/mikeash/MAObjCRuntime/blob/master/main.m #Mejor runtime obj-c, extendible https://github.com/jspahrsummers/libextobjc #Similar https://github.com/Midar/objfw/ #Implementacion de obj-c portable http://swtch.com/~rsc/regexp/regexp1.html #Mejor que regex http://swannodette.github.io/2013/07/12/communicating-sequential-processes/ #Fundamentos CSP
There are several ways to clone a repository from github. Similar from other providers, such as bitbucket, gitlab, etc.
https://git-scm.com/book/en/v2/Git-on-the-Server-The-Protocols
Mostly, we use
This worked on 14/May/23. The instructions will probably require updating in the future.
llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)
Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.
It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.
08737ef720f0510c7ec2aa84d7f70c691073c35d
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