To install MS-DOS 6.22 in Virtual Box, I kept all the defaults settings for a VM type of DOS:
Attaching the first install disk image and powering on, the install starts up:
MS-DOS 6.22 install on Virtual Box
Let’s Encrypt certificate expired on older Macs
I have a number of older machines that I use on a regular basis, so I’m no stranger to the struggles of not being able to browse current websites on older machines with older browsers and the typical SSL/TLS support issues that you run into. I was surprised to see this error this week on my 2008 Mac Pro running Mac OS X 10.11 El Capitan and a latest version of Chrome:
Looking at the certificate for any site not loading it looks like the certificate has expired:
I’m not seeing this on my other later/current machines though, so clearly something on these older machines is no longer getting updates. Browsing around a few other sites and seeing the same issue on many sites so it was not just limited to a single site, so I realized something else was going on. Some Googling found this article:
Following the steps to download the updated certificate from LetsEncrypt and install it into Keychain did the job.
Running aitextgen model training in a Docker container
I’m setting up an approach to run text generation model training jobs on demand with aitextgen, and the first approach I’m looking at is to run the training in a Docker container. Later I may move this to an AWS service like ECS, but this is my first step.
I’ve built a Docker image with the following dockerfile:
FROM amazonlinux RUN yum update -y RUN yum install -y python3 RUN pip3 install aitextgen ADD source-file-for-fine-tuning.txt . ADD generate.py . ADD train.py .
.. and then built my image with:
docker build -t aitextgen .
I then run a container passing in the cmd I want to run, in this case ‘python3 train.py’:
docker run --volume /data/trained_model:/trained_model:rw -d aitextgen sh -c "cd / && python3 train.py && mv aitextgen.tokenizer.json /trained_model"
I’m also attaching a bind point where the model output is being written to during the run, and -d to run the container in the background. The last step in the run command copies the token file to the mounted EBS volume so it can be reused by the generation.
To generate text from the model, run:
docker run --volume /data/trained_model:/trained_model:rw -d aitextgen sh -c "cd / && python3 generate.py"
Mounting a volume from the host into a Docker container
Assuming you have a folder called /data that you want to mount and access within a Docker container, you can so this a couple of ways, but the easiest is to specify when you start the container as a bind mount, with:
docker run –volume /host-path:/container-path:[rw|ro] imagename –volume
More info and options in the docs here.