Post
267
What's this cool purple banner haha 😶😶😶
- 3 replies
Jared Sulzdorf PRO
jsulz
AI & ML interests
Infrastructure, law, policy
Recent Activity
liked
a model
about 8 hours ago
bartowski/Tesslate_Tessa-T1-32B-GGUF
Organizations
jsulz's activity
reacted to
clem's
post with 😎
about 7 hours ago
@pabloce you can check it out over here https://huggingface.co/join/xet :)
reacted to
clem's
post with 🤗
2 days ago
Post
1450
A repository is created every ~15 secs on Hugging Face so
@kramp
added a "Getting Started" to make it easier & a model release checklist: https://huggingface.co/docs/hub/model-release-checklist
What are you uploading today?
What are you uploading today?
- 1 reply
reacted to
tomaarsen's
post with 🔥
2 days ago
Post
1834
‼️Sentence Transformers v4.0 is out! You can now train and finetune reranker models with multi-GPU training, bf16 support, loss logging, callbacks & much more. I also prove that finetuning on your domain helps much more than you might think.
1️⃣ Reranker Training Refactor
Reranker models can now be trained using an extensive trainer with a lot of powerful features:
- MultiGPU Training (Data Parallelism (DP) and Distributed Data Parallelism (DDP))
- bf16 training support; loss logging
- Evaluation datasets + evaluation loss
- Improved callback support + an excellent Weights & Biases integration
- Gradient checkpointing, gradient accumulation
- Model card generation
- Resuming from a training checkpoint without performance loss
- Hyperparameter Optimization
and much more!
Read my detailed blogpost to learn about the components that make up this new training approach: https://huggingface.co/blog/train-reranker
Notably, the release is fully backwards compatible: all deprecations are soft, meaning that they still work but emit a warning informing you how to upgrade.
2️⃣ New Reranker Losses
- 11 new losses:
- 2 traditional losses: BinaryCrossEntropy and CrossEntropy
- 2 distillation losses: MSE and MarginMSE
- 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL
- 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
3️⃣ New Reranker Documentation
- New Training Overview, Loss Overview, API Reference docs
- 5 new, 1 refactored training examples docs pages
- 13 new, 6 refactored training scripts
- Migration guides (2.x -> 3.x, 3.x -> 4.x)
4️⃣ Blogpost
Alongside the release, I've written a blogpost where I finetune ModernBERT on a generic question-answer dataset. My finetunes easily outperform all general-purpose reranker models, even models 4x as big. Finetuning on your domain is definitely worth it: https://huggingface.co/blog/train-reranker
See the full release notes here: https://github.com/UKPLab/sentence-transformers/releases/v4.0.1
1️⃣ Reranker Training Refactor
Reranker models can now be trained using an extensive trainer with a lot of powerful features:
- MultiGPU Training (Data Parallelism (DP) and Distributed Data Parallelism (DDP))
- bf16 training support; loss logging
- Evaluation datasets + evaluation loss
- Improved callback support + an excellent Weights & Biases integration
- Gradient checkpointing, gradient accumulation
- Model card generation
- Resuming from a training checkpoint without performance loss
- Hyperparameter Optimization
and much more!
Read my detailed blogpost to learn about the components that make up this new training approach: https://huggingface.co/blog/train-reranker
Notably, the release is fully backwards compatible: all deprecations are soft, meaning that they still work but emit a warning informing you how to upgrade.
2️⃣ New Reranker Losses
- 11 new losses:
- 2 traditional losses: BinaryCrossEntropy and CrossEntropy
- 2 distillation losses: MSE and MarginMSE
- 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL
- 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
3️⃣ New Reranker Documentation
- New Training Overview, Loss Overview, API Reference docs
- 5 new, 1 refactored training examples docs pages
- 13 new, 6 refactored training scripts
- Migration guides (2.x -> 3.x, 3.x -> 4.x)
4️⃣ Blogpost
Alongside the release, I've written a blogpost where I finetune ModernBERT on a generic question-answer dataset. My finetunes easily outperform all general-purpose reranker models, even models 4x as big. Finetuning on your domain is definitely worth it: https://huggingface.co/blog/train-reranker
See the full release notes here: https://github.com/UKPLab/sentence-transformers/releases/v4.0.1
reacted to
giadap's
post with 🔥
2 days ago
Post
2174
We've all become experts at clicking "I agree" without a second thought. In my latest blog post, I explore why these traditional consent models are increasingly problematic in the age of generative AI.
I found three fundamental challenges:
- Scope problem: how can you know what you're agreeing to when AI could use your data in different ways?
- Temporality problem: once an AI system learns from your data, good luck trying to make it "unlearn" it.
- Autonomy trap: the data you share today could create systems that pigeonhole you tomorrow.
Individual users shouldn't bear all the responsibility, while big tech holds all the cards. We need better approaches to level the playing field, from collective advocacy and stronger technological safeguards to establishing "data fiduciaries" with a legal duty to protect our digital interests.
Available here: https://huggingface.co/blog/giadap/beyond-consent
I found three fundamental challenges:
- Scope problem: how can you know what you're agreeing to when AI could use your data in different ways?
- Temporality problem: once an AI system learns from your data, good luck trying to make it "unlearn" it.
- Autonomy trap: the data you share today could create systems that pigeonhole you tomorrow.
Individual users shouldn't bear all the responsibility, while big tech holds all the cards. We need better approaches to level the playing field, from collective advocacy and stronger technological safeguards to establishing "data fiduciaries" with a legal duty to protect our digital interests.
Available here: https://huggingface.co/blog/giadap/beyond-consent
reacted to
clem's
post with 🔥
9 days ago
Post
2521
Nice new space to see how fast your personal or organization followers are growing on HF:
julien-c/follow-history
As you can see, I still have more followers than @julien-c even if he's trying to change this by building such cool spaces 😝😝😝
julien-c/follow-history
As you can see, I still have more followers than @julien-c even if he's trying to change this by building such cool spaces 😝😝😝
posted
an
update
10 days ago
Post
1798
If you've been following along with the Xet Team's (https://huggingface.co/xet-team) work, you know we've been working to migrate the Hugging Face Hub from Git LFS and to Xet.
Recently, we launched a waitlist to join the movement to Xet (join here! https://huggingface.co/join/xet ) but getting to this point was a journey.
From the initial proof of concept in August, to launching on the Hub internally, to migrating a set of repositories and routing a small chunk of download traffic on the Hub through our infrastructure. Every step of the way has been full of challenges, big and small, and well worth the effort.
Over the past few weeks, with real traffic flowing through our services we’ve tackled some truly gnarly issues (unusual upload/download patterns, memory leaks, load imbalances, and more) and resolved each without major disruptions.
If you're curious about how this sliver of Hub infrastructure looks as we routed traffic through it for the first time (and want a deep dive full of Grafana and Kibana charts 🤓) I have a post for you.
Here's an inside look into the day of our first migrations and the weeks following, where we pieced together solutions in real time.
https://huggingface.co/blog/xet-on-the-hub
Recently, we launched a waitlist to join the movement to Xet (join here! https://huggingface.co/join/xet ) but getting to this point was a journey.
From the initial proof of concept in August, to launching on the Hub internally, to migrating a set of repositories and routing a small chunk of download traffic on the Hub through our infrastructure. Every step of the way has been full of challenges, big and small, and well worth the effort.
Over the past few weeks, with real traffic flowing through our services we’ve tackled some truly gnarly issues (unusual upload/download patterns, memory leaks, load imbalances, and more) and resolved each without major disruptions.
If you're curious about how this sliver of Hub infrastructure looks as we routed traffic through it for the first time (and want a deep dive full of Grafana and Kibana charts 🤓) I have a post for you.
Here's an inside look into the day of our first migrations and the weeks following, where we pieced together solutions in real time.
https://huggingface.co/blog/xet-on-the-hub
reacted to
fdaudens's
post with ❤️👍
10 days ago
Post
2255
Want to build useful newsroom tools with AI? We’re launching a Hugging Face x Journalism Slack channel where journalists turn AI concepts into real newsroom solutions.
Inside the community:
✅ Build open-source AI tools for journalism
✅ Get direct help from the community
✅ Stay updated on new models and datasets
✅ Learn from other journalists’ experiments and builds
The goal? Go from “I read about AI” to “I built an AI tool that supercharged my newsroom.” —no more learning in isolation.
Join us! https://join.slack.com/t/journalistson-tnd8294/shared_invite/zt-30vsmhk4w-dZpeMOoxdhCvfNsqtspPUQ (Please make sure to use a clear identity—no teddybear85, for example 😉)
(If you know people who might be interested, tag them below! The more minds we bring in, the better the tools we build.)
Inside the community:
✅ Build open-source AI tools for journalism
✅ Get direct help from the community
✅ Stay updated on new models and datasets
✅ Learn from other journalists’ experiments and builds
The goal? Go from “I read about AI” to “I built an AI tool that supercharged my newsroom.” —no more learning in isolation.
Join us! https://join.slack.com/t/journalistson-tnd8294/shared_invite/zt-30vsmhk4w-dZpeMOoxdhCvfNsqtspPUQ (Please make sure to use a clear identity—no teddybear85, for example 😉)
(If you know people who might be interested, tag them below! The more minds we bring in, the better the tools we build.)
replied to
their
post
14 days ago
Glad to see you join the waitlist! Welcome aboard 🤗🚀
replied to
their
post
15 days ago
Glad to hear you've signed up! This is for everyone on the Hub. 🤗
You can feel free to sign up for just yourself or your entire organization and see for yourself if there are improvements to your workflow!
We'll let you know more as we roll out access from the waitlist.
reacted to
BrigitteTousi's
post with ❤️🔥🚀
16 days ago
Post
3324
LeRobot goes to driving school! 🚗🚗🚗
Hugging Face just announced a new collab with Yaak to bring the largest open-source self-driving dataset to LeRobot!
Major kudos to HF's @cadene , as well as @sandhawalia , @Shnissen and the Yaak team!
Check out the blog post here: https://huggingface.co/blog/lerobot-goes-to-driving-school
Hugging Face just announced a new collab with Yaak to bring the largest open-source self-driving dataset to LeRobot!
Major kudos to HF's @cadene , as well as @sandhawalia , @Shnissen and the Yaak team!
Check out the blog post here: https://huggingface.co/blog/lerobot-goes-to-driving-school
- 1 reply
posted
an
update
16 days ago
Post
1384
It's finally here ❤️
Build faster than ever with lightning fast upload and download speeds starting today on the Hub ⚡
Xet storage is rolling out access across the Hub - join the waitlist here https://huggingface.co/join/xet
You can apply for yourself, or your entire organization. Head over to your account settings for more information or join anywhere you see the Xet logo on a repository you know.
Have questions? Join the conversation below 👇 or open a discussion on the Xet team page xet-team/README
Build faster than ever with lightning fast upload and download speeds starting today on the Hub ⚡
Xet storage is rolling out access across the Hub - join the waitlist here https://huggingface.co/join/xet
You can apply for yourself, or your entire organization. Head over to your account settings for more information or join anywhere you see the Xet logo on a repository you know.
Have questions? Join the conversation below 👇 or open a discussion on the Xet team page xet-team/README
-
- 6 replies
reacted to
fdaudens's
post with 🤗
18 days ago
Post
5728
Honored to be named among their 12 pioneers and power players in the news industry in the 2025 Tech Trends Report from Future Today Strategy Group.
Incredible group to be part of - each person is doing groundbreaking work at the intersection of AI and journalism. Worth following them all: they're consistently sharing practical insights on building the future of news.
Take the time to read this report, it's packed with insights as always. The news & information section's #1 insight hits hard: "The most substantive economic impact of AI to date has been licensing payouts for a handful of big publishers. The competition will start shifting in the year ahead to separate AI 'haves' that have positioned themselves to grow from the 'have-nots.'"
This AI-driven divide is something I've been really concerned about. Now is the time to build more than ever!
👉 Full report here: https://ftsg.com/wp-content/uploads/2025/03/FTSG_2025_TR_FINAL_LINKED.pdf
Incredible group to be part of - each person is doing groundbreaking work at the intersection of AI and journalism. Worth following them all: they're consistently sharing practical insights on building the future of news.
Take the time to read this report, it's packed with insights as always. The news & information section's #1 insight hits hard: "The most substantive economic impact of AI to date has been licensing payouts for a handful of big publishers. The competition will start shifting in the year ahead to separate AI 'haves' that have positioned themselves to grow from the 'have-nots.'"
This AI-driven divide is something I've been really concerned about. Now is the time to build more than ever!
👉 Full report here: https://ftsg.com/wp-content/uploads/2025/03/FTSG_2025_TR_FINAL_LINKED.pdf
- 2 replies
reacted to
fdaudens's
post with 🔥❤️👍
20 days ago
Post
4095
AI will bring us "a country of yes-men on servers" instead of one of "Einsteins sitting in a data center" if we continue on current trends.
Must-read by @thomwolf deflating overblown AI promises and explaining what real scientific breakthroughs require.
https://thomwolf.io/blog/scientific-ai.html
Must-read by @thomwolf deflating overblown AI promises and explaining what real scientific breakthroughs require.
https://thomwolf.io/blog/scientific-ai.html
- 2 replies
posted
an
update
23 days ago
Post
2081
If you haven't already, I strong recommend reading
@chiphuyen
's AI Engineering https://www.goodreads.com/en/book/show/216848047-ai-engineering
It comes complete with a section on open source AI (of obvious interest to the crowd here) and more than one mention of the Hugging Face community 🤗
In my opinion, one of the best parts is that it is a compendium for seminal and cutting-edge AI resources, with nearly 250 arXiv papers cited. I've done my best to collect them all in a single place, organized by chapter and by order in which they appear in the book:
jsulz/ai-engineering-67c5abe02c8596b5c089934c
Happy reading 🤓
It comes complete with a section on open source AI (of obvious interest to the crowd here) and more than one mention of the Hugging Face community 🤗
In my opinion, one of the best parts is that it is a compendium for seminal and cutting-edge AI resources, with nearly 250 arXiv papers cited. I've done my best to collect them all in a single place, organized by chapter and by order in which they appear in the book:
jsulz/ai-engineering-67c5abe02c8596b5c089934c
Happy reading 🤓