Dreamscale launches streamlined VLA fine-tuning with π0.5 support
arnie_hacker · x · 2026-10-27
pentestduck announces Training on Dreamscale, greatly simplifying fine-tuning of VLA (vision-language-action) models: 1) pick a base model (e.g. π0.5), 2) import your dataset from Hugging Face or local files, 3) start training. This significantly lowers the barrier to fine-tuning robot VLA models.
More from Embodied
- Tesla Robotaxi hits 438K driverless miles/week in Austin, may have passed Waymo — mitchdeg · 2026-10-27
- Tesla Tops Waymo in Austin With 438K Weekly Driverless Miles vs 406K — AccBalanced · 2026-10-27
- Tesla FSD safety report: one major collision per 6M miles, 9x safer than US average — elonmusk · 2026-10-27
- Dream Labs is hiring robot learning researchers in SF, plus security and ops roles — scott_e_reed · 2026-10-27
- Running the π0.5 VLA model locally on a 16GB RTX 4070 Ti SUPER with APXInf — lxfater · 2026-10-27
- Beff Jezos: Elon always frontloads mass production and wins the ramp asymptotically — beffjezos · 2026-10-27