4 ms·
Nice, awhile ago, there was new ai python projects that came out and needed the binaries and the website install wasn't available or documented. Many users did
by IronWolve 3y ago
Nice, awhile ago, there was new ai python projects that came out and needed the binaries and the website install wasn't available or documented.
Many users didnt want to install random binaries (security), and the devs didnt document or link directly to the corp websites.
Now its as easy as pip install, going to make things easier.
The community is moving faster that the corps making the tools.
- machinekob 3y agoONNX is pretty old at least 5 years and its still mostly useful on Nvidia GPU's or x64 CPU. TBH. cool that projects like that are still alive but MLIR looks like the future of proper model storage, and custom format and loading is still a king today cause you can easily modify model and optimise or even fine tune which isn't even possible in ONNX without ton of work (also static spec and versions in protobuf sucks wish they migrate to flatbuffers).
- refulgentis 3y agofor people looking at deploying ML: this comment is not even wrong[1], there's no real way to respond to it substantively. It's sort of like saying Swift came out 7 years ago and it's mostly useful for iPhone X and the first iPad Air. [1] https://en.wikipedia.org/wiki/Not_even_wrong https://en.wikipedia.org/wiki/Not_even_wrong
- machinekob 3y agoOk :)