Instructions to use felsager/smolvla_ms_cube_stack with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use felsager/smolvla_ms_cube_stack with LeRobot:
# See https://github.com/huggingface/lerobot?tab=readme-ov-file#installation for more details git clone https://github.com/huggingface/lerobot.git cd lerobot pip install -e .[smolvla]
# Launch finetuning on your dataset python lerobot/scripts/train.py \ --policy.path=felsager/smolvla_ms_cube_stack \ --dataset.repo_id=lerobot/svla_so101_pickplace \ --batch_size=64 \ --steps=20000 \ --output_dir=outputs/train/my_smolvla \ --job_name=my_smolvla_training \ --policy.device=cuda \ --wandb.enable=true
# Run the policy using the record function python -m lerobot.record \ --robot.type=so101_follower \ --robot.port=/dev/ttyACM0 \ # <- Use your port --robot.id=my_blue_follower_arm \ # <- Use your robot id --robot.cameras="{ front: {type: opencv, index_or_path: 8, width: 640, height: 480, fps: 30}}" \ # <- Use your cameras --dataset.single_task="Grasp a lego block and put it in the bin." \ # <- Use the same task description you used in your dataset recording --dataset.repo_id=HF_USER/dataset_name \ # <- This will be the dataset name on HF Hub --dataset.episode_time_s=50 \ --dataset.num_episodes=10 \ --policy.path=felsager/smolvla_ms_cube_stack - Notebooks
- Google Colab
- Kaggle
Upload policy weights, train config and readme
Browse files- README.md +4 -4
- model.safetensors +1 -1
- train_config.json +6 -6
README.md
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---
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base_model: lerobot/smolvla_base
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datasets: felsager/ManiSkill_StackCube-
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library_name: lerobot
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license: apache-2.0
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model_name: smolvla
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## Training Dataset
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- **Repository:** [felsager/ManiSkill_StackCube-
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- **Episodes:** 1000
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- **Frames:** 107420
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- **Frame rate:** 10 FPS
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- **Task(s):** "StackCube-v1"
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<a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=felsager/ManiSkill_StackCube-
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<img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"/>
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<img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl-dark.svg"/>
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</a>
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| Setting | Value |
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| --- | --- |
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| Training steps |
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| Batch size | 256 |
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| Optimizer | adamw |
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| Learning rate | 0.0001 |
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---
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base_model: lerobot/smolvla_base
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datasets: felsager/ManiSkill_StackCube-v1_mp_recomputed_stats
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library_name: lerobot
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license: apache-2.0
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model_name: smolvla
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## Training Dataset
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- **Repository:** [felsager/ManiSkill_StackCube-v1_mp_recomputed_stats](https://huggingface.co/datasets/felsager/ManiSkill_StackCube-v1_mp_recomputed_stats)
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- **Episodes:** 1000
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- **Frames:** 107420
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- **Frame rate:** 10 FPS
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- **Task(s):** "StackCube-v1"
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<a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=felsager/ManiSkill_StackCube-v1_mp_recomputed_stats">
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<img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"/>
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<img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl-dark.svg"/>
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</a>
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| Setting | Value |
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| --- | --- |
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| Training steps | 2 |
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| Batch size | 256 |
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| Optimizer | adamw |
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| Learning rate | 0.0001 |
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model.safetensors
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train_config.json
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{
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"dataset": {
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"repo_id": "felsager/ManiSkill_StackCube-
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"revision":
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"use_imagenet_stats": true,
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"video_backend": "torchcodec",
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"return_uint8": false,
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"compile_mode": "default"
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"output_dir": "/work/sim_vla_ws/runs/train/
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"prefetch_factor": 4,
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"persistent_workers": true,
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"dataloader_multiprocessing_context": "spawn",
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"compile_mode": "default"
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"output_dir": "/work/sim_vla_ws/runs/train/smolvla_ds_cfg_test",
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"job_name": "smolvla_ds_cfg_test",
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"resume": false,
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"seed": 0,
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"cudnn_deterministic": false,
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