Instructions to use limmin33/opd-rl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use limmin33/opd-rl with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("limmin33/opd-rl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from limmin33/opd-rl: direct link, hf CLI and curl.
- Browser
- Download file 1.97 kB
-
https://huggingface.co/limmin33/opd-rl/resolve/main/README.md
- Command line
-
hf download hf://limmin33/opd-rl/README.md
-
curl -L -o README.md https://huggingface.co/limmin33/opd-rl/resolve/main/README.md
1.97 kB
| library_name: transformers | |
| tags: | |
| - verl | |
| - reinforcement-learning | |
| - agent | |
| - alfworld | |
| # opd-rl checkpoints | |
| Checkpoints are stored four levels deep: | |
| ``` | |
| <environment>/<model>/<training-method>/<checkpoint>/ | |
| ``` | |
| Each checkpoint directory holds the verl FSDP actor state: | |
| ``` | |
| <checkpoint>/actor/model_world_size_<N>_rank_<r>.pt sharded policy weights | |
| <checkpoint>/actor/optim_world_size_<N>_rank_<r>.pt optimizer state (full uploads only) | |
| <checkpoint>/actor/extra_state_world_size_<N>_rank_<r>.pt | |
| <checkpoint>/actor/config.json, tokenizer files | |
| <checkpoint>/data.pt dataloader state | |
| <checkpoint>/hf/ merged HuggingFace weights (when present) | |
| ``` | |
| Merge the shards back into a loadable HuggingFace model with verl: | |
| ```sh | |
| python scripts/model_merger.py merge --backend fsdp \ | |
| --local_dir <checkpoint>/actor --target_dir ./merged | |
| ``` | |
| ## Contents | |
| | environment | model | training method | checkpoint | | |
| |---|---|---|---| | |
| | `alfworld` | `qwen2.5-3b` | `grpo` | `global_step_50` | | |
| | `alfworld` | `qwen2.5-3b` | `rlsd_warmdown_100` | `global_step_150` | | |
| | `alfworld` | `qwen2.5-3b` | `sdar_coef0.01_beta5.0_skillallfalse` | `global_step_150` | | |
| | `alfworld` | `qwen3-1.7b` | `grpo_2gpu` | `global_step_100` | | |
| | `alfworld` | `qwen3-1.7b` | `grpo_2gpu` | `global_step_150` | | |
| | `alfworld` | `qwen3-1.7b` | `grpo_2gpu` | `global_step_50` | | |
| | `alfworld` | `qwen3-1.7b` | `rlsd_warmdown_100` | `global_step_100` | | |
| | `alfworld` | `qwen3-1.7b` | `rlsd_warmdown_100` | `global_step_150` | | |
| | `alfworld` | `qwen3-1.7b` | `rlsd_warmdown_100` | `global_step_50` | | |
| | `alfworld` | `qwen3-1.7b` | `sdar_coef0.01_beta5.0_skillallfalse` | `global_step_100` | | |
| | `alfworld` | `qwen3-1.7b` | `sdar_coef0.01_beta5.0_skillallfalse` | `global_step_150` | | |
| | `alfworld` | `qwen3-1.7b` | `sdar_coef0.01_beta5.0_skillallfalse` | `global_step_50` | | |
| Uploaded with `scripts/upload_checkpoints_to_hf.py` (`--content full`). | |