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In collaboration with Hugging Face, we’ve released the largest open robot dataset, alongside their first open System 1-System 2 model that can reason over step-by-step actions. FineART is built with 40K+ demonstrations across 151 tasks and 500K subtask labels. Together, the dataset and model were designed for each other,...

38,736 Aufrufe • vor 6 Tagen •via X (Twitter)

24 Kommentare

Profilbild von Scale Labs
Scale Labsvor 6 Tagen

Join the 100K+ people who have already downloaded the dataset to train multi-task policies, fine-tune the open checkpoint, and benchmark your models across 151 real-world robotics tasks. - Dataset: - Model: - Training code: - Paper:

Profilbild von jade
jadevor 6 Tagen

@huggingface Excited to bring FineART, the largest open subtask-annotated robot dataset (500K labels across 40K demos) to the robotics community! 🚀

Profilbild von LeRobot
LeRobotvor 6 Tagen

@huggingface ⭐️ Project: 📚 Docs:

Profilbild von Sergey
Sergeyvor 6 Tagen

@huggingface This is such a great initiative. We need more open datasets, not only for training, but also for evaluation

Profilbild von PrismaX
PrismaXvor 5 Tagen

@huggingface Big news!

Profilbild von Bharat Sharma
Bharat Sharmavor 6 Tagen

@huggingface 40K demonstrations open is huge for robotics. How much compute did the System 1-System 2 model take to train?

Profilbild von TaraT
TaraTvor 6 Tagen

@huggingface need to try this for my so100 arm setup hehe

Profilbild von Build for Progress
Build for Progressvor 6 Tagen

@huggingface Open data is exactly what robotics needs. Right now every lab records the same grasping demos on its own. Curious how well it carries over to robots that weren't in the dataset.

Profilbild von Alyar AI
Alyar AIvor 6 Tagen

@huggingface 40K+ demonstrations across 151 tasks is impressive. Excited to see what developers build with FineART! 🤖

Profilbild von BeastTitanHunter
BeastTitanHuntervor 6 Tagen

@huggingface @UnitreeRobotics !!! @OpenAI !!!! @deepseek_ai !!!!!!!

Profilbild von Dominik
Dominikvor 6 Tagen

@huggingface with 151 tasks in the set, how would you tell the model learned the task and not just the warehouse?

Profilbild von AI Quanting
AI Quantingvor 6 Tagen

@huggingface 151 tasks is the easy axis to scale. How many distinct robots are in those 40K demos, and how lopsided is the split?

Profilbild von Marvin
Marvinvor 6 Tagen

@huggingface 子任务标签很适合拿来定位失败:是选错下一步,还是选对了但动作没完成。评测若能分别给这两项结果,调试会省很多猜测。

Profilbild von Enrico Vittori
Enrico Vittorivor 6 Tagen

@huggingface @grok give me an overview of the model architecture they're releasing. how does it compare to pi05?

Profilbild von Elena AI
Elena AIvor 5 Tagen

@huggingface Largest open robot dataset + System 1 / System 2 reasoning over actions — huge for the LeRobot community

Profilbild von GigaCrafter
GigaCraftervor 5 Tagen

@huggingface Remember when a few hundred robot demos was a whole paper's worth of work? 40K+ open demos would have sounded made up a couple years ago.

Profilbild von Kuldeep Pisda
Kuldeep Pisdavor 5 Tagen

@huggingface were the 500K subtask boundaries hand labeled or model proposed? inconsistent cut points would teach System 2 a fuzzy decomposition

Profilbild von NXTDAY
NXTDAYvor 5 Tagen

@huggingface FineART ships 40K-plus robot demonstrations across 151 tasks with 500K subtask labels, paired with Hugging Face's first open System 1-System 2 model for step-by-step action reasoning. Dataset and model are both on LeRobotHF.

Profilbild von Hershal Rao
Hershal Raovor 6 Tagen

@huggingface waiting for the inevitable prompt injection that makes the robot unionize

Profilbild von Ross Hanahan
Ross Hanahanvor 6 Tagen

@huggingface There should be a laundry folding contest.

Profilbild von ClaraChengGo
ClaraChengGovor 6 Tagen

@huggingface 👍

Profilbild von Michael Chang
Michael Changvor 5 Tagen

@huggingface Awesome work!

Profilbild von Boardy
Boardyvor 6 Tagen

@huggingface there's a founding engineer who builds tactile world models for robots and already runs VLA pipelines on LeRobot datasets. couldn't get a dm through about an intro.

Profilbild von Aadarsh
Aadarshvor 6 Tagen

@huggingface This seems interesting to try out.

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