Instructions to use lerobot/being_h05_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use lerobot/being_h05_base with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Remove embodiment-specific adapter metadata
Browse files- README.md +3 -1
- config.json +0 -1
- policy_postprocessor.json +2 -4
- policy_preprocessor.json +0 -1
README.md
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@@ -38,7 +38,9 @@ weights.
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The checkpoint preserves Being-H0.5's fixed semantic 200D state/action slots,
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validity masks, three-camera processing, raw task string, and four-step
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flow-matching sampler.
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## Usage
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The checkpoint preserves Being-H0.5's fixed semantic 200D state/action slots,
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validity masks, three-camera processing, raw task string, and four-step
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flow-matching sampler. It consumes the named state and action fields from the
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released model contract; an environment-specific vector adapter is not
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included.
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## Usage
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config.json
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"num_inference_steps": 4,
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"prompt_template": "According to the instruction '{task_description}', what's the micro-step actions in the next {k} steps?",
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"metadata": {},
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"atomic_4_adapter": false,
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"optimizer_lr": 2e-05,
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"optimizer_weight_decay": 0.0,
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"scheduler_warmup_steps": 1000,
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"num_inference_steps": 4,
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"prompt_template": "According to the instruction '{task_description}', what's the micro-step actions in the next {k} steps?",
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"metadata": {},
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"optimizer_lr": 2e-05,
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"optimizer_weight_decay": 0.0,
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"scheduler_warmup_steps": 1000,
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policy_postprocessor.json
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"steps": [
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{
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"registry_name": "being_h05_semantic_unpack",
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"config": {
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"atomic_4_adapter": false
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}
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},
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{
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"registry_name": "device_processor",
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}
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}
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]
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}
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"steps": [
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{
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"registry_name": "being_h05_semantic_unpack",
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"config": {}
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},
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{
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"registry_name": "device_processor",
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}
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}
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]
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}
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policy_preprocessor.json
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],
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"prompt_template": "According to the instruction '{task_description}', what's the micro-step actions in the next {k} steps?",
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"chunk_size": 16,
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"atomic_4_adapter": false,
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"state_slots": {
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"eef_position": [
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0,
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],
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"prompt_template": "According to the instruction '{task_description}', what's the micro-step actions in the next {k} steps?",
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"chunk_size": 16,
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"state_slots": {
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"eef_position": [
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0,
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