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Jared Sulzdorf PRO

jsulz

https://www.jsulz.com/

AI & ML interests

Infrastructure, law, policy

Recent Activity

reacted to danieldk's post with 🤗 about 5 hours ago

We have been working on a project called `kernels`. `kernels` makes it possible to load compute kernels directly from the Hub! 🚀 We plan to give kernels a more proper introduction soon. But for those who have been following along, we are happy to announce a new release: - New layer API with `torch.compile` support. - Experimental support for loading Apple Silicon Metal 🤘 Kernels. - Generate wheels from Hub kernels for legacy deployments. Full release notes here: https://github.com/huggingface/kernels/releases/tag/v0.6.0

reacted to danieldk's post with 🔥 about 5 hours ago

upvoted an article 2 days ago

Improving Hugging Face Model Access for Kaggle Users

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reacted to danieldk's post with 🤗🔥 about 5 hours ago

Post

1393

We have been working on a project called kernels. kernels makes it possible to load compute kernels directly from the Hub! 🚀

We plan to give kernels a more proper introduction soon. But for those who have been following along, we are happy to announce a new release:

- New layer API with torch.compile support.
- Experimental support for loading Apple Silicon Metal 🤘 Kernels.
- Generate wheels from Hub kernels for legacy deployments.

Full release notes here: https://github.com/huggingface/kernels/releases/tag/v0.6.0

upvoted an article 2 days ago

Article

Improving Hugging Face Model Access for Kaggle Users

and 4 others •

24 days ago

• 27

replied to their post 4 days ago

Hey @RichardErkhov we've begun onboarding you to Xet! 🚀

All new repos you create will be Xet-enabled by default and your existing repos are being migrated as we speak.

Since you have a lot of repos the migration of existing content may take some time. While it's ongoing you may notice instances where a repo is a mixture of LFS and Xet-backed files. This shouldn't be an problem due to how we manage backwards compatibility, but if you have any issues, please let me know here.

For new repos you create, just make sure to follow the instructions here to get the full benefits of using Xet storage.

I'll follow up here once all of your repos have been moved over!

replied to reach-vb's post 4 days ago

Hey @mradermacher sorry for the delay; just wanted to let you know that your migration to Xet should be complete!

Feel free to ping me here if you have any questions or feedback. Excited to hear how it's been going! 🤗

Also, if you have any issues, don't hesitate to open a discussion here https://huggingface.co/spaces/xet-team/README/discussions or an issue on this repo https://github.com/huggingface/xet-core

updated a collection 10 days ago

Papers (I want) To Read

Collection

A list of papers on my reading list. • 30 items • Updated 10 days ago

posted an update 10 days ago

Post

359

With major model families like

Qwen and all of Llama from

meta-llama on Xet, the time is right for new users and organizations to say goodbye to LFS on the Hub.

Xet is now the default storage for new AI builders 🚀 🚀 🚀

Just sign up for an account, create a new model or dataset, pip install huggingface_hub and you're off to the races!

Read more here https://huggingface.co/changelog/xet-default-for-new-users

And for everyone with existing repositories, just sign up here https://huggingface.co/join/xet - we'll migrate all existing repositories to Xet and all new repos you create will be Xet-backed by default.

New activity in xet-team/README 11 days ago

got my first xet error , and it leaks a token (i think?)

#2 opened 20 days ago by

Tonic

reacted to merve's post with 🤗🔥🚀 14 days ago

Post

3097

Bu post'u çevirebilirsiniz 🤗💗

6 replies

replied to reach-vb's post 14 days ago

Hey @mradermacher just wanted to let you know that we've begun onboarding you to Xet!

All new repos that you create will be Xet-enabled by default. We are still migrating existing repos, so you will see times when there are a mixture of LFS and Xet files side-by-side, but as the migration progresses everything will become Xet.

As I mentioned in my last message, none of this is an issue due to how we've designed the system for backward compatibility, but if you have any questions or concerns, please let me know. Otherwise, I'll follow up here once all your repos are migrated!

reacted to celinah's post with 😎🤗🚀 14 days ago

Post

2214

✨ Today we’re releasing Tiny Agents in Python — an MCP-powered Agent in ~70 lines of code 🐍

Inspired by Tiny Agents in JS from @julien-c , we ported the idea to Python and integrated it directly into huggingface_hub — with a built-in MCP Client and a Tiny Agents CLI.

TL;DR: With MCP (Model Context Protocol), you can expose tools like web search or image generation and connect them directly to LLMs. It’s simple — and surprisingly powerful.

pip install "huggingface_hub[mcp]>=0.32.0"

We wrote a blog post where we show how to run Tiny Agents, and dive deeper into how they work and how to build your own.
👉 https://huggingface.co/blog/python-tiny-agents

1 reply

upvoted an article 14 days ago

Article

Tiny Agents in Python: a MCP-powered agent in ~70 lines of code

and 3 others •

15 days ago

• 122

upvoted 2 changelogs 14 days ago

Changelog

Static Spaces can now have a build step

14 days ago

• 91

Changelog

Xet is now the default storage option for new users and organizations

14 days ago

• 58

replied to their post 16 days ago

Woohoo!! Thanks for joining ❤️ I'll onboard you from the waitlist soon and follow up here when done.

Will do on the storage side - I'm also quite curious.

If you have any questions or feedback, don't hesitate to ping me here 🤗

posted an update 17 days ago

Post

2127

Heyo @RichardErkhov the

xet-team at Hugging face was wondering if you wanted to join the fun and jump over to Xet storage. 🤗

We've been onboarding folks https://huggingface.co/blog/xet-on-the-hub know the backend can scale (Llama 4 and Qwen 3 are on Xet), is great for working with quants (see xet-team/quantization-dedup ), and we're pushing on inviting impactful orgs and users on the Hub. You fit the bill.

We'd love to onboard you, get some feedback, and create some excitement 🎉

The steps are pretty straightforward - join the waitlist at hf.co/join/xet and we'll take care of the rest.

The system is fully backward compatible, so you shouldn't notice a thing. BUT to get the best experience when uploading/downloading, make sure you have hf_xet installed alongside the latest huggingface_hub

What do you think?

4 replies