| --- |
| license: apache-2.0 |
| pretty_name: trainnr research artifacts |
| tags: |
| - robotics |
| - reinforcement-learning |
| - mujoco |
| - system-identification |
| size_categories: |
| - n<1K |
| --- |
| |
| # trainnr research artifacts |
|
|
| The model checkpoints (`*.pt`) and study logs (`*.log`) that the |
| [trainnr](https://github.com/Trainnr-AI/trainnr) findings records cite. They are |
| not in the code repository: they would add over 100 MB to every clone and plugin |
| install. |
|
|
| Each file sits at the path it has in the repository (`docs/artifacts/...`), so |
| downloading this dataset into a checkout's root puts every file where a record |
| expects it. [`MOVED.tsv`](MOVED.tsv) lists every file with its path, size and |
| SHA-256. |
|
|
| ## Download |
|
|
| From the root of a trainnr checkout: |
|
|
| ```sh |
| uvx --from huggingface_hub hf download trainnr/trainnr-artifacts \ |
| --repo-type dataset --include "docs/*" --local-dir . |
| ``` |
|
|
| Then check the files against the manifest: |
|
|
| ```sh |
| grep -v '^#' docs/artifacts/MOVED.tsv | awk -F'\t' '{print $3" "$1}' | sha256sum -c |
| ``` |
|
|
| ## What is here |
|
|
| - `docs/artifacts/walk-c1/`: the final checkpoint (`model_7999.pt`) of each of |
| the 15 arms of the microduck walk-c1 study (point, narrow, wide, identified |
| and point-refit, three seeds each). |
| - `docs/artifacts/lift-studies/`: the study logs of the SO-101 lift studies. |
| - `docs/artifacts/dagger/`: the DAgger round's data generation log. |
|
|
| Every run's `identity.json` in the repository names its robot, actuator and fit |
| by their stamps. |
|
|
| A `.pt` file is a Python pickle: load it with |
| `torch.load(path, weights_only=True)`, as trainnr does. |
|
|
| ## Licence |
|
|
| These files are part of trainnr and are licensed under the Apache License 2.0 |
| (see `LICENSE`). Revisions made available alongside trainnr releases up to and |
| including 0.2.0-rc.2 were under the Functional Source License, Version 1.1, ALv2 |
| Future License. |
|
|
| The microduck checkpoints were trained on Pollen Robotics' microduck model |
| (Apache-2.0; its meshes are Creative Commons BY-NC-SA) with BAM actuator fits |
| (Rhoban, Apache-2.0). Third-party material is listed in the repository's |
| [NOTICE](https://github.com/Trainnr-AI/trainnr/blob/main/NOTICE). |
|
|
