⭐ The first foundational model available on LeRobot ⭐ Pi0 is the most advanced Vision Language Action model. It takes natural language commands as input and directly output autonomous behavior. It was trained by Physical Intelligence and ported to pytorch by Pablo Montalvo 👇🧵

Take a look at the code:

You can now download and use the pretrained policy just like transformers: policy = Pi0Policy.from_pretrained("lerobot/pi0") action =

Even cooler, you can finetune it directly on your dataset. Here is an example with @DAubakirovaa 's dataset: python lerobot/scripts/train.py \ --policy.path=lerobot/pi0 \ --dataset.repo_id=danaaubakirova/koch_test Visualize her dataset here:

The original code in Jax is available over here:

We have full blog post with more details!

Announcing: Our most advanced speech-to-text model goes beyond accuracy to capture the real-world complexity of human conversation and deliver reliable, source-of-truth audio data. Explore Universal-2 updates 👇

@LeRobotHF @physical_int @m_olbap that is so cool , Thanks @LeRobotHF ! Is this model somewhat similar to OpenVLA (which is also on hugging face) ? For instance with OpenVLA we get action output tokens for a single armed robot. Can i simply replace OpenVLA with this without changing the inference pipeline ?

@LeRobotHF @physical_int @m_olbap Pi0 was trained with much more data! Yes you should be as our policy includes all the preprocessing and post processing. Only requirements: images need to be in float32 [0,1] range.

@LeRobotHF @physical_int @m_olbap Incredible gift!

@LeRobotHF @physical_int @m_olbap Super. The LLM moment for Robotics is here. The gap is closing fast. Eagerly awaiting for the weights. Also, would be great to have some blog or tutorial on how one can do this from scratch.

@LeRobotHF @physical_int @m_olbap We ported the weights already. We are working on a tutorial to reproduce this on more affordable robots