RLinf-Pi05-BEHAVIOR-1K-PT50-CS32
This repository contains the shared Pi0.5 BEHAVIOR checkpoint used by the RPent BEHAVIOR integration.
The RPent policy profile id is:
pi05-b1kpt50-cs32
Files
The runtime-critical files are:
model.safetensors
config.json
assets/behavior-1k/2025-challenge-demos/norm_stats.json
A duplicate normalization statistics file is also included at:
physical-intelligence/behavior/norm_stats.json
This duplicate mirrors the LIBERO-style physical-intelligence/... checkpoint
layout. The canonical BEHAVIOR runtime path remains
assets/behavior-1k/2025-challenge-demos/norm_stats.json.
Checksums
7e257666d835f6af701de493676a6c86a0421b2efc737a0f911d782b7a09f635 model.safetensors
a4ae208203adfdd64c5fdbd4b0dc257e4ebbc82e464cb146dd0377051b25fc0a config.json
d66ed16830a98f90dde8a315058b4a0df59f5e05734c1686d8b3f66787d0a929 assets/behavior-1k/2025-challenge-demos/norm_stats.json
d66ed16830a98f90dde8a315058b4a0df59f5e05734c1686d8b3f66787d0a929 physical-intelligence/behavior/norm_stats.json
Configuration
config.json:
{
"action_dim": 32,
"action_horizon": 32,
"paligemma_variant": "gemma_2b",
"action_expert_variant": "gemma_300m",
"precision": "bfloat16"
}
RPent BEHAVIOR uses the pi05_behavior OpenPI configuration. The policy emits
32-dimensional chunks and RPent maps them to the BEHAVIOR environment action
contract.
Download
Install the Hugging Face CLI:
pip install -U huggingface_hub
Download the checkpoint:
hf download RLinf/RLinf-Pi05-BEHAVIOR-1K-PT50-CS32 \
--local-dir ./checkpoints/RLinf-Pi05-BEHAVIOR-1K-PT50-CS32
export PI05_CHECKPOINT_PATH="$PWD/checkpoints/RLinf-Pi05-BEHAVIOR-1K-PT50-CS32"
Optional checksum verification:
cd "$PI05_CHECKPOINT_PATH"
sha256sum model.safetensors config.json \
assets/behavior-1k/2025-challenge-demos/norm_stats.json \
physical-intelligence/behavior/norm_stats.json
Intended Use
This checkpoint is intended for research use with RPent BEHAVIOR. It is not a general-purpose language model and should be evaluated only through the BEHAVIOR/RPent robotics stack.
For BEHAVIOR evaluation, official task success is determined by the simulator's
task success signal, exposed in RPent as task_success from
info["done"]["success"]. Primitive-level success, reward, video appearance,
or local workflow completion are not substitutes for official success.
Related Links
- RPent: https://github.com/RLinf/RPent
- RLinf: https://github.com/RLinf/RLinf
- RLinf Hugging Face organization: https://huggingface.co/RLinf
- LIBERO counterpart: https://huggingface.co/RLinf/RLinf-Pi05-LIBERO-130-fullshot-SFT
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