Robotics
LeRobot
Safetensors
robot-control
vision-language-action
vla
dm05
visual-memory
supervised-fine-tuning
Instructions to use Dexmal/DM05-Lerobot-MEM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use Dexmal/DM05-Lerobot-MEM with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 1,052 Bytes
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"all_values_bit_identical": true,
"dtype_preserved": "BF16",
"only_omitted_tensor": [
"model.vlm.model.language_model.embed_tokens.weight"
],
"portable_config_and_processor_paths": true
},
"runtime": {
"offline_load_empty_hf_cache": true,
"normalization_checks": 8,
"full_history_frames": 20,
"training_loss": 0.5122761130332947,
"history_gradients_nonzero": true,
"vision_gradients_nonzero": true,
"explicit_chunk_shape": [
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"current_only_chunk_rejected": true,
"control_frames": 26,
"public_prediction_calls": 2,
"duplicate_history": false,
"episode_reset": true,
"gpu": "NVIDIA RPBZZZ6",
"peak_allocated_gib": 20.550536632537842,
"weights_not_updated": true
},
"task_success_rate": null,
"scope": "Base-weight conversion and execution validation; no optimizer updates or task benchmark"
}
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