Andrej Karpathy: Nice and especially appreciate the r...| Robocrunch AI

Nice and especially appreciate the release of the accompanying logbooks, detailing the struggles of training transformers at scale https://t.co/GErHySLdCJ https://t.co/Nks3rvMLi8
— Andrej Karpathy (@karpathy) May 4, 2022

Happy to share that we have updated and published v2 of our "efficient transformer" survey! Major updates: ✅ Expanded our scope to sparse models and added a ton of new models! ✅ Wrote a retrospective post about the advances in the past year. Link:https://t.co/nAaTLG8wOp

Shared by Yi Tay at 3/15/2022

FYI: our self-training code has been merged into the @huggingface's Transformers library https://t.co/B47rp6eYSP. Thanks, @GuggerSylvain for helping out!

Shared by Tu Vu at 4/13/2022

Our graph Transformer has been accepted as a Contributed Talk to NeurIPS ML and Physical Sciences workshop (TOP 3 out of 151) 😀😀😀 Check out the paper and youtube video https://t.co/BGeP71L3ls https://t.co/mlyZLnYoYh Due to scheduling issues, we will only present a poster.

Shared by Dominique Beaini at 11/11/2021

Thanks to all of you that have helped with the @huggingface OSS Survey in January! According to the results, we've defined some roadmaps for the: - TensorFlow part of 🤗 Transformers - 🤗 Datasets library - Docs of 🤗 Transformers Join the conversation: https://t.co/Eww8ZDk6AU

Shared by Lysandre at 3/10/2022

Next stop on the tour is embeddings. These are what save transformers from being impossibly unwieldy. https://t.co/NeqtbwO9xw

Shared by Brandon Rohrer at 11/11/2021

Very excited to share a line of work on documentation for applied RL systems. Introducing, Reward Reports for Reinforcement Learning Paper: https://t.co/OHBBZH7ewx Template: https://t.co/gDfbOGTeuk Blog Post: https://t.co/w9p1OXJsgG Workshop June 11: https://t.co/ulp7ZQu86r 🧵

Shared by Nathan Lambert at 4/29/2022

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