import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Miical/pi05-base", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]PI0.5 Base — GigaModels PyTorch Conversion
This repository contains a PyTorch Diffusers-format conversion of the Physical Intelligence PI0.5 base checkpoint. The weights were converted from the official OpenPI JAX checkpoint with the following script from open-gigaai/giga-models:
No additional fine-tuning was applied to these base weights. The tokenizer files are colocated with the converted policy so consumers can use one Hub repository for both the policy and tokenizer.
Loading with GigaModels
from giga_models import PI0Policy
policy = PI0Policy.from_pretrained("Miical/pi05-base")
Loading with verl-vla
Set the model path directly to the Hub repository:
cluster:
actor_rollout_ref:
model:
path: Miical/pi05-base
Normalization statistics are embodiment- and dataset-specific and are not
included in this base checkpoint. Configure model.adapter.norm_stats_path
when training or evaluating with verl-vla.
Attribution and license
The conversion implementation is provided by GigaModels under Apache-2.0. Use and redistribution of the converted weights remain subject to the terms applicable to the original PI0.5 checkpoint and its underlying components. Please also cite the original PI0/PI0.5 work as requested by the GigaModels documentation.
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