Upload policy weights, train config and readme

README.md

@@ -0,0 +1,70 @@
+---
+datasets: thewisp/pick_place_earplug
+library_name: lerobot
+license: apache-2.0
+model_name: pi05
+pipeline_tag: robotics
+tags:
+- pi05
+- lerobot
+- robotics
+---
+
+# Model Card for pi05
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+**π₀.₅ (Pi05) Policy**
+
+π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
+
+**Model Overview**
+
+π₀.₅ represents a significant evolution from π₀, developed by Physical Intelligence to address a big challenge in robotics: open-world generalization. While robots can perform impressive tasks in controlled environments, π₀.₅ is designed to generalize to entirely new environments and situations that were never seen during training.
+
+For more details, see the [Physical Intelligence π₀.₅ blog post](https://www.physicalintelligence.company/blog/pi05).
+
+
+This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
+See the full documentation at [LeRobot Docs](https://huggingface.co/docs/lerobot/index).
+
+---
+
+## How to Get Started with the Model
+
+For a complete walkthrough, see the [training guide](https://huggingface.co/docs/lerobot/il_robots#train-a-policy).
+Below is the short version on how to train and run inference/eval:
+
+### Train from scratch
+
+```bash
+lerobot-train \
+  --dataset.repo_id=${HF_USER}/<dataset> \
+  --policy.type=act \
+  --output_dir=outputs/train/<desired_policy_repo_id> \
+  --job_name=lerobot_training \
+  --policy.device=cuda \
+  --policy.repo_id=${HF_USER}/<desired_policy_repo_id>
+  --wandb.enable=true
+```
+
+_Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`._
+
+### Evaluate the policy/run inference
+
+```bash
+lerobot-record \
+  --robot.type=so100_follower \
+  --dataset.repo_id=<hf_user>/eval_<dataset> \
+  --policy.path=<hf_user>/<desired_policy_repo_id> \
+  --episodes=10
+```
+
+Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a local or hub checkpoint.
+
+---
+
+## Model Details
+
+- **License:** apache-2.0

config.json

@@ -40,7 +40,7 @@
     "private": null,
     "tags": null,
     "license": null,
-    "pretrained_path": "lerobot/pi05_base",
+    "pretrained_path": "outputs/pi05_training/checkpoints/last/pretrained_model",
     "paligemma_variant": "gemma_2b",
     "action_expert_variant": "gemma_300m",
     "dtype": "bfloat16",

train_config.json

@@ -108,7 +108,7 @@
         "private": null,
         "tags": null,
         "license": null,
-        "pretrained_path": "lerobot/pi05_base",
+        "pretrained_path": "outputs/pi05_training/checkpoints/last/pretrained_model",
         "paligemma_variant": "gemma_2b",
         "action_expert_variant": "gemma_300m",
         "dtype": "bfloat16",
@@ -151,7 +151,7 @@
     },
     "output_dir": "outputs/pi05_training",
     "job_name": "pi05_training",
-    "resume": false,
+    "resume": true,
     "seed": 1000,
     "num_workers": 4,
     "batch_size": 2,