Instructions to use IDEAS-Lab-Northwestern/pi05-sim-table-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use IDEAS-Lab-Northwestern/pi05-sim-table-lora with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Add checkpoint manifest
Browse files- README.md +42 -0
- checkpoint_manifest.json +33 -0
README.md
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---
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library_name: openpi
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tags:
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- openpi
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- pi0.5
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- lora
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- lerobot
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- robotics
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---
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# OpenPI pi0.5 LoRA on sim-table
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This repository stores OpenPI checkpoints for the `pi05_clutter_libero_lora`
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training run on `IDEAS-Lab-Northwestern/sim-table`.
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The checkpoint layout mirrors OpenPI's local checkpoint tree so later training
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checkpoints can be appended without reshaping the repo:
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```text
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checkpoints/
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pi05_clutter_libero_lora/
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sim_table_lora/
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3000/
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_CHECKPOINT_METADATA
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params/
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train_state/
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assets/
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```
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To add another checkpoint later, upload the new numeric step directory to the
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same run path. For example:
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```bash
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UV_CACHE_DIR=/tmp/uv-cache-sim-table \
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uv run huggingface-cli upload IDEAS-Lab-Northwestern/pi05-sim-table-lora \
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checkpoints/pi05_clutter_libero_lora/sim_table_lora/4000 \
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checkpoints/pi05_clutter_libero_lora/sim_table_lora/4000 \
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--repo-type model \
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--commit-message "Add checkpoint step 4000"
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```
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The associated LeRobot dataset is `IDEAS-Lab-Northwestern/sim-table`.
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checkpoint_manifest.json
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{
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"repo_id": "IDEAS-Lab-Northwestern/pi05-sim-table-lora",
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"repo_type": "model",
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"created_utc": "2026-04-29T19:41:54Z",
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"source_git_commit": "650c5b0283a49c42784fb5055a0507da2c6d347d",
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"train_config_name": "pi05_clutter_libero_lora",
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"experiment_name": "sim_table_lora",
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"dataset_repo_id": "IDEAS-Lab-Northwestern/sim-table",
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"checkpoint_base_path": "checkpoints/pi05_clutter_libero_lora/sim_table_lora",
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"checkpoints": [
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{
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"step": 3000,
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"path": "checkpoints/pi05_clutter_libero_lora/sim_table_lora/3000",
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"local_source": "checkpoints/pi05_clutter_libero_lora/sim_table_lora/3000",
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"size": "9.0G",
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"files": 27
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}
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],
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"model": {
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"family": "pi0.5",
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"action_dim": 32,
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"action_horizon": 16,
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"paligemma_variant": "gemma_2b_lora",
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"action_expert_variant": "gemma_300m_lora",
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"discrete_state_input": false
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},
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"training": {
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"num_train_steps": 20000,
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"batch_size": 4,
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"ema_decay": null,
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"base_checkpoint": "gs://openpi-assets/checkpoints/pi05_base/params"
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}
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}
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