Papers I Have Read
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A list of papers that have moved off my reading list
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9 items
โข
Updated
Jared Sulzdorf PRO
jsulz
AI & ML interests
Infrastructure, law, policy
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Papers I Have Read
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Papers I Have Read
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jsulz's activity
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about 8 hours ago
reacted to
fdaudens's
post with โค๏ธ
1 day ago
Post
5641
๐ฏ Perplexity drops their FIRST open-weight model on Hugging Face: A decensored DeepSeek-R1 with full reasoning capabilities. Tested on 1000+ examples for unbiased responses.
Check it out: perplexity-ai/r1-1776
Blog post: https://perplexity.ai/hub/blog/open-sourcing-r1-1776
Check it out: perplexity-ai/r1-1776
Blog post: https://perplexity.ai/hub/blog/open-sourcing-r1-1776
- 1 reply
xet repositories
2
#1 opened 1 day ago
by
Tonic
posted
an
update
2 days ago
Post
2708
Time flies!
Six months after joining Hugging Face the Xet team is kicking off the first migrations from LFS to our storage for a number of repositories on the Hub.
More on the nitty gritty details behind the migration soon, but here are the big takeaways:
๐ค We've successfully completed the first migrations from LFS -> Xet to test the infrastructure and prepare for a wider release
โ No action on your part needed - you can work with a Xet-backed repo like any other repo on the Hub (for now - major improvements on their way!)
๐ Keep an eye out for the Xet logo to see if a repo you know is on our infra! See the screenshots below to spot the difference ๐
โฉ โฉ โฉ Blazing uploads and downloads coming soon. Wโre gearing up for a full integration with the Hub's Python library that will make building on the Hub faster than ever - special thanks to @celinah and @Wauplin for their assistance.
๐ Want Early Access? If youโre curious and want to test it out the bleeding edge that will power the development experience on the Hub, weโd love to partner with you. Let me know!
This is the culmination of a lot of effort from the entire team. Big round of applause to @sirahd @brianronan @jgodlewski @hoytak @seanses @assafvayner @znation @saba9 @rajatarya @port8080 @yuchenglow
Six months after joining Hugging Face the Xet team is kicking off the first migrations from LFS to our storage for a number of repositories on the Hub.
More on the nitty gritty details behind the migration soon, but here are the big takeaways:
๐ค We've successfully completed the first migrations from LFS -> Xet to test the infrastructure and prepare for a wider release
โ No action on your part needed - you can work with a Xet-backed repo like any other repo on the Hub (for now - major improvements on their way!)
๐ Keep an eye out for the Xet logo to see if a repo you know is on our infra! See the screenshots below to spot the difference ๐
โฉ โฉ โฉ Blazing uploads and downloads coming soon. Wโre gearing up for a full integration with the Hub's Python library that will make building on the Hub faster than ever - special thanks to @celinah and @Wauplin for their assistance.
๐ Want Early Access? If youโre curious and want to test it out the bleeding edge that will power the development experience on the Hub, weโd love to partner with you. Let me know!
This is the culmination of a lot of effort from the entire team. Big round of applause to @sirahd @brianronan @jgodlewski @hoytak @seanses @assafvayner @znation @saba9 @rajatarya @port8080 @yuchenglow
- 1 reply
reacted to
christopher's
post with ๐ฅ
2 days ago
Post
1687
The folks at Foursquare released a dataset of 104.5 million places of interest (
foursquare/fsq-os-places) and here's all of them on a plot
- 4 replies
upvoted
2
articles
4 days ago
Article
Welcome Fireworks.ai on the Hub ๐
โข
52
Article
Introducing Three New Serverless Inference Providers: Hyperbolic, Nebius AI Studio, and Novita ๐ฅ
โข
87
liked
a
model
4 days ago
liked
a
model
5 days ago
reacted to
davanstrien's
post with ๐ฅโค๏ธ
8 days ago
Post
1836
How do you make 1M+ Hugging Face models & datasets more discoverable?
davanstrien/Smol-Hub-tldr!
I fine-tuned HuggingFaceTB/SmolLM2-360M to generate one-line summaries from a model or dataset README.
Its own self-description?
"A model for generating concise summaries of model & dataset cards from the Hugging Face Hub"
The goal? Make it easier to find the right models and datasets for your specific needs. It's already powering a semantic search for datasets Space.
It's still a WIP but thanks to @loubnabnl , @anton-l , @eliebak et al, for cooking such a nice base model for fine-tuning small, efficient models for specific domains and tasks. ๐
davanstrien/Smol-Hub-tldr!
I fine-tuned HuggingFaceTB/SmolLM2-360M to generate one-line summaries from a model or dataset README.
Its own self-description?
"A model for generating concise summaries of model & dataset cards from the Hugging Face Hub"
The goal? Make it easier to find the right models and datasets for your specific needs. It's already powering a semantic search for datasets Space.
It's still a WIP but thanks to @loubnabnl , @anton-l , @eliebak et al, for cooking such a nice base model for fine-tuning small, efficient models for specific domains and tasks. ๐
reacted to
m-ric's
post with ๐ฅ
10 days ago
Post
4693
"๐ฎ๐ฌ๐ฎ๐ฑ ๐๐ถ๐น๐น ๐ฏ๐ฒ ๐๐ต๐ฒ ๐๐ฒ๐ฎ๐ฟ ๐ผ๐ณ ๐๐ ๐ฎ๐ด๐ฒ๐ป๐๐": this statement has often been made, here are numbers to support it.
I've plotted the progress of AI agents on GAIA test set, and it seems they're headed to catch up with the human baseline in early 2026.
And that progress is still driven mostly by the improvement of base LLMs: progress would be even faster with fine-tuned agentic models.
I've plotted the progress of AI agents on GAIA test set, and it seems they're headed to catch up with the human baseline in early 2026.
And that progress is still driven mostly by the improvement of base LLMs: progress would be even faster with fine-tuned agentic models.