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ninjaoden/
pi05_base_fp32

Name: pi05_base_fp32
Rating: 2.5 (9 reviews)

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π₀.₅ - Base

This is a PyTorch version of the PI0.5 pi05_base model, converted from the original JAX/Flax implementation.

Model Details

Architecture: PI0.5 (Vision-Language-Action model with discrete state input)
Model Type: PI0.5
Domain: Base model (general purpose)
Precision: 32-bit floating point (fp32)
Vision Model: PaliGemma (gemma_2b)
Action Expert: gemma_300m

Key Features

Discrete State Input: Uses discrete language tokens for state representation
Flow Matching: Utilizes adaRMSNorm for timestep injection in action expert
Enhanced Action Modeling: Improved action prediction with flow matching approach

Conversion Details

This model was converted from JAX to PyTorch using the OpenPI conversion script:

bash

python examples/convert_jax_model_to_pytorch.py \
    --checkpoint_dir /pi05_base \
    --config_name pi05_base \
    --output_path /pi05_base/pytorch/fp32/ \
    --precision float32

Usage

python

from openpi.models_pytorch.pi0_pytorch import PI0Pytorch
import torch

# Load the model
model = PI0Pytorch.from_pretrained("pepijn223/pi05_base_fp32")

# The model expects inputs in the format:
# - images: torch.Tensor of shape [batch, height, width, channels]  
# - text: tokenized text prompts
# - proprioceptive_state: robot state information (if applicable)

Model Architecture

The model consists of:

Vision Encoder: PaliGemma-based vision processing
Language Encoder: Text prompt understanding
Action Expert: Specialized network for action prediction
Integration Layer: Combines multimodal information for action output

Training Data

This model was trained on robotics datasets appropriate for its domain:

DROID models: Trained on diverse robot manipulation data
LIBERO models: Trained on diverse tabletop manipulation scenarios
Base models: Trained on general robotics datasets

Limitations

Model performance depends on similarity between deployment and training environments
May require domain-specific fine-tuning for optimal performance
Action space must match the trained action dimension (32)

Citation

If you use this model, please cite the original OpenPI work:

bibtex

@article{openpi2024,
    title={Open-World Robotic Manipulation with Vision-Language-Action Models},
    author={Physical Intelligence},
    year={2024},
    url={https://github.com/Physical-Intelligence/openpi}
}

Original Repository

OpenPI GitHub Repository

License

This model follows the same license as the original OpenPI repository.

ninjaoden/pi05_base_fp32