It's rather off-topic at this point, but I've never understood how HF can afford to be a CDN for such huge files. It seems like enterprise customers must be subsidizing a lot, but...at that point, is there not a cheaper alternative that doesn't subsidize every hobbyist and startup around?

> I'm just waiting for some corporate IP law firm to learn about Huggingface.

Presumably they already know. The issue is that IP law firms are tiny compared to the trillions of capital pouring into "AI". And if you believe the USA is a capitalist country where the side with deeper pockets win, you know you're not going to win against the trillionaires.

Why is the text field in dataset preview table populated with pornographic labels?

Nemotron is mostly open data. They only release a portions of their pre-training data. From https://docs.nvidia.com/nemotron/latest/nemotron/super3/pret...

  Open-source data coverage: The released datasets cover an estimated 8–10T tokens 
  (~40–50% of the internal 25T blend). Missing categories include code (~14% of blend),
  nemotron-cc-code (~2%), crawl++ (~2%), and academic text (~2%). Users should 
  supplement with their own data for these categories and adjust train_iters 
  accordingly.

Nemotron is the strongest model (on most benchmarks) that has its full training pipeline and most of the data open. Olmo 3 from AllenAI, and K2 Think V2 from Mohamed bin Zayed University of Artificial Intelligence are both fully open, but not as capable as the Nemotron family. Granite has much of the training pipeline and data open, but is missing some of each.