HF has become the best storage platform for PRIVATE and PUBLIC models and datasets, both intermediary and final ones! Great example from @heyjasperai who used HF buckets to store their Monet dataset and train models directly on it!

More details: https://huggingface.co/storage/testimonials/jasperai

.@dh7net, SVP of Image Research, said it best: "The HF infra is a no-brainer."

A big unlock for teams working with large datasets for training, especially when they update over time. Read how Jasper used @huggingface as the creation and storage backbone for MONET: https://huggingface.co/storage/testimonials/jasperai

@julien_c Love it!

@heyjasperai @dh7net @huggingface Hf infra for training with large shifting datasets is definitely the way.

Makes you wonder what else is sitting on that storage backbone waiting to be tapped.

@ClementDelangue @heyjasperai That's why we love HuggingFace 🤗🫂

@ClementDelangue @heyjasperai this is such a clean way to manage large datasets.

@ClementDelangue @heyjasperai using HF buckets for training directly is the part that actually moves the needle

datasets that just sit on the shelf are useless

@ClementDelangue @heyjasperai wait, HF datasets for training AND storage?

ngl thats actually a clean workflow compared to glueing together four services

@ClementDelangue @heyjasperai wait so ur telling me i could store my dataset AND train on the same platform without managing infra

finally some actual use case for storage in web3