Hugging Face
Models
Datasets
Spaces
Buckets
Docs
Enterprise
Pricing
Website
Tasks
HuggingChat
Collections
Languages
Organizations
Community
Blog
Posts
Daily Papers
Hardware
Learn
Discord
Forum
GitHub
Solutions
Team & Enterprise
Hugging Face PRO
Enterprise Support
Inference Providers
Inference Endpoints
Storage Buckets
Log In
Sign Up
13.6
TFLOPS
Eren Ata
PRO
ErenAta00
3
19
38
Follow
enigmind021's profile picture
risedangel's profile picture
SeaWolf-AI's profile picture
19 followers
ยท
35 following
https://xrlab.cbu.edu.tr
ErenAta16
eren-ata-3287991a7
AI & ML interests
None yet
Recent Activity
reacted
to
alphabell-research
's
post
with ๐
about 12 hours ago
One number missing from LFM3's on-device story: memory at 256K context. Liquid AI reports 1.90 GB peak on iPhone 17 Pro at 32K. From the pinned config, f16 K/V cache alone would be 0.41 GB at 32K, 1.61 GB at 128K and 3.22 GB at 256K, before weights and runtime buffers. The chart shows the calculation, not a phone measurement. If you have run longer contexts on-device, share peak memory and time to first token here: https://huggingface.co/LiquidAI/LFM3-1.7B/discussions/5 Model: https://huggingface.co/LiquidAI/LFM3-1.7B
liked
a dataset
about 15 hours ago
nvidia/PhysicalAI-WorldModel-Synthetic-Warehouse-Operations-Scenes
replied
to
their
post
3 days ago
Maverick 1.1 is out. When we released the first version, the feedback was clear: real people do not give one clean command at a time. They change their minds, they point and say "put that on the shelf", they ask for a lamp that is in another room, and sometimes the one speaking is a remote expert helping someone on site. 1.1 is built around that. - Say "no, the other one" and it undoes the last action and repeats it on the other object. If the effect can't be undone, like a button that was already pressed, it tells you. - It sees what people are looking at or pointing at, and who is speaking. - It finds objects in other rooms, goes there and acts, or asks which one if there are two. - It follows a short plan in one sentence: "open the cabinet, put the book and the alarm clock in it, then close it". In the clip, a remote expert corrects the model, then asks it to highlight what the technician is looking at. On test sets we sealed before training and ran once, the new abilities score 93 to 100%, where 1.0 scores 33 to 87%. On sentences written by people (the ALFRED set) the two versions are level, at 83.2% and 83.8%. Where it still falls short: in unfamiliar situations it tends to act when it should ask, and a remote speaker can act in the scene with no permission check, so your app has to enforce that. Same 4B model and licence (Apache-2.0), the same 11 tools plus `undo`, still offline on a 4 GB laptop GPU. The Unity package for the new scene format (1.1.0) is on GitHub: https://github.com/mcbu-xrlab/Maverick-Unity Model: https://huggingface.co/ErenAta00/Maverick-4B-Unity-XR-Agent-1.1 Article and full demo: https://huggingface.co/blog/ErenAta00/maverick-1-1-undo-pointing-other-rooms Built at the Extended Reality Laboratory (XRLab), Manisa Celal Bayar University: https://huggingface.co/ExtendedRealityLabMCBU
View all activity
Organizations
ErenAta00
's datasets
2
Sort:ย Recently updated
ErenAta00/turkish-phishsoc-50k
Preview
โข
Updated
Jun 7
โข
77
โข
1
ErenAta00/VOID-Quadmask-Dataset
Viewer
โข
Updated
Apr 11
โข
43.2k
โข
910
โข
1