---
pretty_name: Franka pi0.5 checkpoint backups
tags:
  - robotics
  - franka
  - pi05
  - checkpoints
---

# π0.5 checkpoint backups

Complete backup checkpoints for the Franka Button Order, Pick3, and Shuffle experiments.

**5,000, 10,000, and 12,500-step milestones remain standalone models at their original addresses in [fm-dev](https://huggingface.co/fm-dev).** Other saved checkpoints are grouped here. Training continues to save every 1,000 steps, and future intermediate checkpoints are uploaded directly to these folders.

## Browse backups

All backups are under [checkpoints/](https://huggingface.co/datasets/fm-dev/pi05-checkpoint-backups/tree/main/checkpoints):

```text
checkpoints/
  r1/<task>/<method>/step6250/
  r2/<task>/<method>/step<number>/
```

| Field | Values |
|---|---|
| Task | `button_order`, `pick3`, `shuffle` |
| Method | `baseline`, `uniform32`, `status_d` |
| Round 1 | Original experiments; final 6,250-step checkpoints are archived here, with 5k models retained separately |
| Round 2 | Execution-only action supervision, 12,500 updates, global batch 4 on 4 GPUs; 5k/10k/12.5k remain separate models |

Each folder preserves the complete original checkpoint bundle. Round-two bundles include inference weights, assets, source, dependency versions, and full optimizer/RNG/sampler resume state. The migrated file contents were verified against the original repositories using their existing Git/LFS identities and sizes before the original intermediate model repositories were removed.

`migration-index.json` maps repositories moved during the initial cleanup to their archive folders. New training uploads appear directly in the directory tree.

## Load a milestone

For example, download the Pick3 Status-D 10k model:

```bash
hf download fm-dev/pi05-pick3-status-d-lora-gbs4-pgb1-gpu4-r2-step10000 --local-dir ./pick3-10k
```

Follow its README and dependency instructions, then load from the downloaded checkpoint directory:

```python
from load_model import load
policy = load()
```

Task-specific history, Writer, and Status inference inputs are documented in each checkpoint's README.

## Recover a backup

Download just the required checkpoint folder:

```bash
hf download fm-dev/pi05-checkpoint-backups --type dataset \
  --include 'checkpoints/r2/pick3/status_d/step9000/**' \
  --local-dir ./pi05-backups
```

The complete bundle is then in `pi05-backups/checkpoints/r2/pick3/status_d/step9000/`. Its loading entry point and saved resume state are preserved.

The original model cards and evaluation limitations remain in the individual folders. A saved checkpoint or successful load does not establish physical robot success rate.