Instructions to use Yang2001/ckpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yang2001/ckpt with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Yang2001/ckpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Yang2001/ckpt: direct link, hf CLI and curl.
- Browser
- Download file 700 Bytes
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https://huggingface.co/Yang2001/ckpt/resolve/main/README.md
- Command line
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hf download hf://Yang2001/ckpt/README.md
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curl -L -o README.md https://huggingface.co/Yang2001/ckpt/resolve/main/README.md
700 Bytes
| library_name: transformers | |
| tags: [robotics, opendm, dm05, xpolicylab] | |
| # Checkpoints | |
| ## `opendm/sim_exam-piper-l1-m1-piper-joint-0` | |
| DM0.5 (OpenDM) full SFT on the sim-exam dual Piper L1 split (900 episodes, 1,636,232 frames), | |
| initialized from `DM05-MEM`. Experiment M1: 15,000 steps x global batch 256 | |
| (8 x H20, micro-batch 8, gradient accumulation 4), lr 5e-5, 1,000 warmup steps, | |
| cosine to 2.5e-5. Action space: `piper` / `joint`. | |
| Files are the final export (inference weights, `config.json`, `norm_stats.json`, processor and | |
| tokenizer, plus `training_config.json` / `training_dataset.json` / `trainer_state.json` for provenance). | |
| Load the directory with the XPolicyLab `OpenDM` adapter. | |