---
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}
}
```