Post-Training Isaac GR00T N1.5 for LeRobot SO-101 Arm

LeRobot v0.6.0: Imagine, Evaluate, Improve

LeRobot v0.4.0: Supercharging OSS Robot Learning

`LeRobotDataset:v3.0`: Bringing large-scale datasets to `lerobot`

Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets

From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot

Non-engineers guide: Train a LLaMA 2 chatbot

LeRobot Community Datasets: The “ImageNet” of Robotics — When and How?

SmolVLA: Efficient Vision-Language-Action Model trained on Lerobot Community Data

From PyTorch DDP to Accelerate to Trainer, mastery of distributed training with ease

Fantastic Pretraining Optimizers and Where to Find Them II: Hyperball Optimization

arXiv:2606. 16899v1 Announce Type: new Abstract: Matrix based optimizers such as Muon can substantially speed up language model pretraining, but their gains over AdamW are observed to shrink as model size and data scale grow when using standard constant decoupled weight decay.

LeRobot goes to driving school: World’s largest open-source self-driving dataset

PLoRA: Efficient Concurrent LoRA Training for Large Language Models

arXiv:2508. 02932v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has gained popularity as a fine-tuning approach for Large Language Models (LLMs) due to its low resource requirements and good performance.