Instructions to use kfstiger/policy_behavior_pi0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use kfstiger/policy_behavior_pi0 with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload policy weights, train config and readme
Browse files- README.md +1 -1
- config.json +1 -1
- model.safetensors +1 -1
- train_config.json +3 -3
README.md
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@@ -5,9 +5,9 @@ license: apache-2.0
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model_name: pi0
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pipeline_tag: robotics
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tags:
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- lerobot
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- pi0
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-
- robotics
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---
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# Model Card for pi0
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model_name: pi0
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pipeline_tag: robotics
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tags:
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- robotics
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- lerobot
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- pi0
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---
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# Model Card for pi0
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config.json
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@@ -56,7 +56,7 @@
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"time_sampling_offset": 0.001,
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"min_period": 0.004,
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"max_period": 4.0,
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-
"use_relative_actions":
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"relative_exclude_joints": [
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"gripper"
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],
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"time_sampling_offset": 0.001,
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"min_period": 0.004,
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"max_period": 4.0,
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"use_relative_actions": true,
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"relative_exclude_joints": [
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"gripper"
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],
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model.safetensors
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 8892502944
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version https://git-lfs.github.com/spec/v1
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oid sha256:4f4ae006f8b9ae21156f1ab49adea59aea054a69537bc0248714da95ce07e3e5
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size 8892502944
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train_config.json
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@@ -138,7 +138,7 @@
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"time_sampling_offset": 0.001,
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"min_period": 0.004,
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"max_period": 4.0,
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-
"use_relative_actions":
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"relative_exclude_joints": [
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"gripper"
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],
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"scheduler_decay_lr": 2.5e-06,
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"tokenizer_max_length": 48
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},
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"output_dir": "outputs/train/
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"job_name": "pi0_behavior",
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"resume": false,
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"seed": 1000,
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"cudnn_deterministic": false,
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"num_workers": 12,
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"batch_size": 8,
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"steps":
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"eval_freq": 20000,
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"log_freq": 200,
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"tolerance_s": 0.0001,
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"time_sampling_offset": 0.001,
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"min_period": 0.004,
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"max_period": 4.0,
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"use_relative_actions": true,
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"relative_exclude_joints": [
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"gripper"
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],
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"scheduler_decay_lr": 2.5e-06,
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"tokenizer_max_length": 48
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},
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"output_dir": "outputs/train/train_behavior_pi0_relative",
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"job_name": "pi0_behavior",
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"resume": false,
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"seed": 1000,
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"cudnn_deterministic": false,
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"num_workers": 12,
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"batch_size": 8,
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"steps": 10000,
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"eval_freq": 20000,
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"log_freq": 200,
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"tolerance_s": 0.0001,
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