if you combine some “special” bits along with token embeding by ihfft, you may have to retrain the entire damn network. also in order to make way for special bits, you may have to introduce extra linear layer.
some may prefer “LoRA”? by only introducing few tunable params and changing the overall output?
we may not annotate anything in our dataset. in contrast, we will set goals and make multiple interfaces for our model to explore.
you can add special task specific embedding before passing to main model, then minus that task specific embedding after passing to classification model.
file sharing and communication
make sure you don’t share important files as read/write on VM.
you may host some “execution server” on UTM VMs. you may expose your very large hard disk using WebDAV server. i think x11vnc and other vnc server may suffice for linux, but we always want to listen to the real operational data, including human operation/intervention, not just those in VNC protocols.
for Ubuntu ARM VM, mss failed on wayland but pyautogui works in both cases. write one python script to pipe raw images to ffmpeg for better compression ratio by shell. the final video is not “time-accurate”. it is frame by frame, matched with timestamps.
forcing ubuntu to use xorg by: sudo vim /etc/gdm3/custom.conf
resize UTM VM disks
you need to first resize the virtio disk in utm setting, then resize partition by using gparted, then update the device mapper
chatgpt sucks. it seems a tailored search engine. it might help filter out useless information. no zeroday exploits (rasp like openrasp) since it does not interact with program and hooks.