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license: other
library_name: pytorch
tags:
- robotics
- libero
- imitation-learning
- world-action-model
- pfd
- privileged-foresight-distillation
---
# PFD LIBERO 12x12 Checkpoint
This repository contains the LIBERO 12x12 PFD checkpoint for **Privileged Foresight Distillation: Zero-Cost Future Correction for World Action Models**.
- Code: https://github.com/PengchengFang-cs/PFD
- Paper: https://arxiv.org/abs/2604.25859
- Checkpoint: `libero_pfd_action512_partial_12x12_step62000.pt`
- Model config: `config.yaml`
- Dataset normalization stats: `dataset_stats.json`
The Python package in the code release is still named `fastwam` for compatibility with the original training and evaluation paths.
## Model
- Task: `libero_uncond_2cam224_1e-4`
- Model config: `fastwam_pfd_action512_partial`
- PFD stage: `s1`
- PFD training mode: `action512_partial`
- Partial trainable depth: action last 12 layers, video last 12 layers
- Base initialization: `libero_uncond_2cam224.pt`
- Training batch size: 32
- Training epochs: 30
- Selected checkpoint step: 62000
## LIBERO Evaluation
Full-suite LIBERO evaluation used 50 trials per task over 40 tasks:
| Suite | Successes | Success Rate |
| --- | ---: | ---: |
| LIBERO-Spatial | 493 / 500 | 98.60% |
| LIBERO-Object | 496 / 500 | 99.20% |
| LIBERO-Goal | 496 / 500 | 99.20% |
| LIBERO-10 | 477 / 500 | 95.40% |
| Overall | 1962 / 2000 | 98.10% |
The corresponding evaluation records are included under `eval/`.
## Download
```bash
pip install -U huggingface_hub
huggingface-cli download AmberJar/PFD \
libero_pfd_action512_partial_12x12_step62000.pt \
config.yaml \
dataset_stats.json \
eval/summary.json \
eval/task_success_rates.csv \
--local-dir ./checkpoints/pfd_libero_12x12_step62000
```
## Evaluation Command
From the PFD code repository:
```bash
export DIFFSYNTH_MODEL_BASE_PATH="$(pwd)/checkpoints"
export DIFFSYNTH_SKIP_DOWNLOAD=true
export LIBERO_CONFIG_PATH="$(pwd)/.libero_scratch"
python experiments/libero/run_libero_manager.py \
task=libero_uncond_2cam224_1e-4 \
model=fastwam_pfd_action512_partial \
ckpt=./checkpoints/pfd_libero_12x12_step62000/libero_pfd_action512_partial_12x12_step62000.pt \
EVALUATION.dataset_stats_path=./checkpoints/pfd_libero_12x12_step62000/dataset_stats.json \
EVALUATION.num_trials=50 \
MULTIRUN.num_gpus=8 \
model.pfd.partial_unfreeze.action_last_layers=12 \
model.pfd.partial_unfreeze.video_last_layers=12
```
## Integrity
See `SHA256SUMS` and `manifest.json` for file hashes and provenance.
## Citation
```bibtex
@article{fang2026pfd,
title={Privileged Foresight Distillation: Zero-Cost Future Correction for World Action Models},
author={Fang, Pengcheng and Chen, Hongli and Cai, Xiaohao},
journal={arXiv preprint arXiv:2604.25859},
year={2026}
}
```
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