Instructions to use maskjp/pi05_piper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use maskjp/pi05_piper with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload policy weights, train config and readme
Browse files- README.md +1 -1
- config.json +4 -4
- model.safetensors +1 -1
- train_config.json +9 -9
README.md
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@@ -5,9 +5,9 @@ license: apache-2.0
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model_name: pi05
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pipeline_tag: robotics
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tags:
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- pi05
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- robotics
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-
- lerobot
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---
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# Model Card for pi05
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model_name: pi05
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pipeline_tag: robotics
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tags:
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- lerobot
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- pi05
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- robotics
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---
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# Model Card for pi05
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config.json
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7
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]
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},
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"observation.images.
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"type": "VISUAL",
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"shape": [
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3,
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640
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]
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},
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"observation.images.
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"type": "VISUAL",
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"shape": [
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3,
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"gradient_checkpointing": true,
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"compile_model": true,
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"compile_mode": "max-autotune",
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"freeze_vision_encoder":
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"train_expert_only":
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"optimizer_lr": 2.5e-05,
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"optimizer_betas": [
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0.9,
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7
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]
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},
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"observation.images.left": {
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"type": "VISUAL",
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"shape": [
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3,
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640
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]
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},
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"observation.images.wrist": {
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"type": "VISUAL",
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"shape": [
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3,
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"gradient_checkpointing": true,
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"compile_model": true,
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"compile_mode": "max-autotune",
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"freeze_vision_encoder": false,
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"train_expert_only": false,
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"optimizer_lr": 2.5e-05,
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"optimizer_betas": [
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0.9,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 9354050752
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version https://git-lfs.github.com/spec/v1
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oid sha256:9324296a32f7eaef433d8acbae90b3c27da21241a31092a708d2173a3c4f141f
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size 9354050752
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train_config.json
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{
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"dataset": {
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"repo_id": "maskjp/piper_pick_new",
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"root":
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"episodes": null,
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"image_transforms": {
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"enable": false,
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},
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"observation.images.
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"type": "VISUAL",
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"shape": [
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3,
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640
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},
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"observation.images.
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"type": "VISUAL",
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"shape": [
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3,
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"gradient_checkpointing": true,
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"compile_model": true,
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"compile_mode": "max-autotune",
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"freeze_vision_encoder":
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"train_expert_only":
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"optimizer_lr": 2.5e-05,
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"optimizer_betas": [
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0.9,
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"scheduler_decay_steps": 30000,
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"scheduler_decay_lr": 2.5e-06
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},
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"output_dir": "outputs/
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"job_name": "
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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": 4,
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"batch_size":
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"steps": 3000,
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"eval_freq": 20000,
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"log_freq": 200,
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"project": "lerobot",
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"entity": null,
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"notes": null,
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"run_id": "
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"mode": null,
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"add_tags": true
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},
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{
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"dataset": {
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"repo_id": "maskjp/piper_pick_new",
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"root": "./piper_pick_new",
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"episodes": null,
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"image_transforms": {
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"enable": false,
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7
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]
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},
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"observation.images.left": {
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"type": "VISUAL",
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"shape": [
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3,
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640
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]
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},
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"observation.images.wrist": {
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"type": "VISUAL",
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"shape": [
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3,
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"gradient_checkpointing": true,
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"compile_model": true,
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"compile_mode": "max-autotune",
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"freeze_vision_encoder": false,
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"train_expert_only": false,
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"optimizer_lr": 2.5e-05,
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"optimizer_betas": [
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0.9,
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"scheduler_decay_steps": 30000,
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"scheduler_decay_lr": 2.5e-06
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},
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"output_dir": "outputs/piper_pick_new_pi052",
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"job_name": "piper_pick_new_pi052",
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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": 4,
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"batch_size": 24,
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"steps": 3000,
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"eval_freq": 20000,
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"log_freq": 200,
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"project": "lerobot",
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"entity": null,
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"notes": null,
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"run_id": "oca0crrd",
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"mode": null,
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"add_tags": true
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},
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