mkdir osm
wget -O osm/planet.mbtiles https://hidrive.ionos.com/api/sharelink/download?id=SYEgScrRe
podman run -ti --rm -p 9000:9000 --name sms -v $(pwd)/osm/:/data/ registry.gitlab.com/markuman/sms:latest
firefox http://localhost:9000
# THIS LINUX SETUP SCRIPT HAS MORPHED INTO A WHOLE PROJECT: HTTPS://OMAKUB.ORG | |
# PLEASE CHECKOUT THAT PROJECT INSTEAD OF THIS OUTDATED SETUP SCRIPT. | |
# | |
# | |
# Libraries and infrastructure | |
sudo apt update -y | |
sudo apt install -y \ | |
docker.io docker-buildx \ | |
build-essential pkg-config autoconf bison rustc cargo clang \ |
{ | |
"Version": "2012-10-17", | |
"Statement": [ | |
{ | |
"Effect": "Deny", | |
"Action": [ | |
"logs:CreateLogGroup", | |
"logs:CreateLogStream", | |
"logs:PutLogEvents" | |
], |
VERSION = \"1.0.0\" | |
PREFIX ?= out | |
INCDIR = inc | |
SRCDIR = src | |
LANG = c | |
OBJDIR = .obj | |
MODULE = binary_name | |
CC = gcc |
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.
- Clone llama.cpp from git, I am on commit
08737ef720f0510c7ec2aa84d7f70c691073c35d
.
- removed
EntityChoiceList
- removed
$manager
(2nd) and$class
(3th) arguments ofORMQueryBuilderLoader
- removed passing a query builder closure to
ORMQueryBuilderLoader
- removed
loader
andproperty
options of theDoctrineType
- deprecated interface
Symfony\Component\HttpKernel\Log\LoggerInterface
has been removed
For us, PHPStan became a bit slower with every release. We have a very large codebase with 10.000+ classes. There seem to be a few known issues related to big arrays.
See: phpstan/phpstan#8353 phpstan/phpstan#8146
To understand which files are problematic we run the following command:
<?php | |
namespace Tests\Integration; | |
use Symfony\Bundle\FrameworkBundle\Test\KernelTestCase; | |
use Symfony\Component\Config\FileLocator; | |
use Symfony\Component\DependencyInjection\ContainerBuilder; | |
use Symfony\Component\DependencyInjection\Definition; | |
use Symfony\Component\DependencyInjection\Loader\XmlFileLoader; |