Instructions to use scy-cell/pi05test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use scy-cell/pi05test with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload policy weights, train config and readme
Browse files- README.md +1 -1
- adapter_config.json +2 -2
- adapter_model.safetensors +2 -2
- config.json +8 -5
- train_config.json +22 -16
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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- lerobot
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-
- robotics
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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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- robotics
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- pi05
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- lerobot
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---
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# Model Card for pi05
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adapter_config.json
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"base_model_class": "PI05Policy",
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"parent_library": "lerobot.policies.pi05.modeling_pi05"
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},
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"base_model_name_or_path": "lerobot/
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"peft_type": "LORA",
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"peft_version": "0.18.1",
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"qalora_group_size": 16,
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"r":
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"rank_pattern": {},
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"revision": null,
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"target_modules": "(.*\\.gemma_expert\\..*\\.self_attn\\.(q|v)_proj|model\\.(state_proj|action_in_proj|action_out_proj|action_time_mlp_in|action_time_mlp_out))",
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"base_model_class": "PI05Policy",
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"parent_library": "lerobot.policies.pi05.modeling_pi05"
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},
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"base_model_name_or_path": "lerobot/pi05_libero_finetuned",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"peft_type": "LORA",
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"peft_version": "0.18.1",
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"qalora_group_size": 16,
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"r": 2,
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"rank_pattern": {},
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"revision": null,
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"target_modules": "(.*\\.gemma_expert\\..*\\.self_attn\\.(q|v)_proj|model\\.(state_proj|action_in_proj|action_out_proj|action_time_mlp_in|action_time_mlp_out))",
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adapter_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
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version https://git-lfs.github.com/spec/v1
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oid sha256:4b410c2504ed69d53a27cddfe797c1ebad84d2e5e3665498d27e0ee767b98100
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size 656312
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config.json
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"pretrained_path": "lerobot/
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"paligemma_variant": "gemma_2b",
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"action_expert_variant": "gemma_300m",
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"dtype": "
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"chunk_size": 50,
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"max_state_dim": 32,
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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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"gripper"
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"empty_cameras": 0,
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"tokenizer_max_length": 200,
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"normalization_mapping": {
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"VISUAL": "IDENTITY",
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"STATE": "QUANTILES",
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"ACTION": "QUANTILES"
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"gradient_checkpointing": true,
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"compile_model":
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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":
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"pretrained_path": "lerobot/pi05_libero_finetuned",
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"paligemma_variant": "gemma_2b",
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"action_expert_variant": "gemma_300m",
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"dtype": "bfloat16",
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"chunk_size": 50,
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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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"empty_cameras": 0,
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"tokenizer_max_length": 200,
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"state_token_companding": "identity",
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"state_token_companding_gain": 2.0,
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"state_token_clip_before_discretize": false,
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"normalization_mapping": {
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"VISUAL": "IDENTITY",
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"STATE": "QUANTILES",
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"ACTION": "QUANTILES"
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"gradient_checkpointing": true,
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"compile_model": false,
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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": 1e-06,
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"optimizer_betas": [
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train_config.json
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"obs_type": "pixels_agent_pos",
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"pretrained_path": "lerobot/
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"paligemma_variant": "gemma_2b",
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"action_expert_variant": "gemma_300m",
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"dtype": "
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"optimizer_lr":
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"optimizer_betas": [
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0.9,
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0.95
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"seed": 1000,
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"cudnn_deterministic": false,
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"num_workers": 4,
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"save_freq":
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"use_policy_training_preset": true,
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"type": "adamw",
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"betas": [
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"type": "cosine_decay_with_warmup",
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"eval": {
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"pretrained_path": "lerobot/pi05_libero_finetuned",
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"dtype": "bfloat16",
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