Instructions to use Miical/pi05-libero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Miical/pi05-libero with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Miical/pi05-libero", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
PI0.5 LIBERO โ OpenPI JAX Checkpoint Conversion
This repository contains a PyTorch Diffusers-format conversion of the PI0.5 LIBERO JAX checkpoint provided by the official Physical Intelligence OpenPI repository. The weights in this repository were not fine-tuned by verl-vla.
The OpenPI JAX checkpoint was converted with the following implementation from open-gigaai/giga-models:
The converted checkpoint is stored in the native Diffusers PI0Policy layout.
Tokenizer files are colocated with the 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-libero")
Loading with verl-vla
Set the model path directly to the Hub repository and point the LIBERO embodiment adapter to the included normalization statistics:
cluster:
actor_rollout_ref:
model:
path: Miical/pi05-libero
adapter:
embodiment: libero
norm_stats_path: /path/to/norm_stats.json
Normalization statistics
norm_stats.json contains the state and action normalization values associated
with the converted OpenPI checkpoint. The values were extracted unchanged from
the source checkpoint configuration and moved into a separate artifact so
config.json only describes the policy architecture.
Download norm_stats.json together with the checkpoint and pass its local path
through model.adapter.norm_stats_path when using the policy with verl-vla.
Attribution and license
The source checkpoint is provided by the Physical Intelligence OpenPI project. The PyTorch 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 follow the citation and attribution guidance from OpenPI and GigaModels.
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