Upload policy weights, train config and readme

README.md

@@ -1,86 +1,62 @@
 ---
-datasets:
-- lerobot/aloha_sim_transfer_cube_human
-language: en
+datasets: lerobot/aloha_sim_transfer_cube_human
 library_name: lerobot
 license: apache-2.0
+model_name: diffusion
+pipeline_tag: robotics
 tags:
-- robotics
-- imitation-learning
 - diffusion
-- mujoco
-- pytorch_model_hub_mixin
+- robotics
+- lerobot
 ---
 
-# DIFFUSION Policy — diffusion_aloha_transfer_cube_seed42
-
-Trained with [LeRobot](https://github.com/huggingface/lerobot).  
-Date: `2026-05-14 11:05`  
-Policy type: `diffusion` | Device: `cuda`
-
----
+# Model Card for diffusion
 
-## 📦 Dataset
+<!-- Provide a quick summary of what the model is/does. -->
 
-| Parameter | Value |
-|---|---|
-| `dataset.repo_id` | `lerobot/aloha_sim_transfer_cube_human` |
 
----
+[Diffusion Policy](https://huggingface.co/papers/2303.04137) treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.
 
-## 🏋️ Training Config
 
-| Parameter | Value |
-|---|---|
-| `steps` | `5` |
-| `batch_size` | `8` |
-| `eval_freq` | `2` |
-| `save_freq` | `1` |
-| `num_workers` | `4` |
-| `seed` | `42` |
-| `eval.n_episodes` | `2` |
-| `eval.batch_size` | `10` |
+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).
 
 ---
 
-## 📐 Policy Architecture
+## How to Get Started with the Model
 
-_All defaults — no overrides applied._
+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
 
-## 🎯 Eval Config
+```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
+```
 
-| Parameter | Value |
-|---|---|
-| `env.type` | `aloha` |
-| `env.task` | `AlohaTransferCube-v0` |
-| `eval.n_episodes` | `5` |
-| `eval.batch_size` | `1` |
-| `eval.use_async_envs` | `False` |
-| `policy.path` | `/kaggle/working/outputs/train/aloha_transfer_cube_seed42/checkpoints/last/pretrained_model` |
+_Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`._
 
----
+### Evaluate the policy/run inference
 
-## 📊 Eval Results
+```bash
+lerobot-record \
+  --robot.type=so100_follower \
+  --dataset.repo_id=<hf_user>/eval_<dataset> \
+  --policy.path=<hf_user>/<desired_policy_repo_id> \
+  --episodes=10
+```
 
-| Metric | Value |
-|---|---|
-| Episodes | `5` |
-| Success rate | `20.0%` |
-| Avg sum reward | `1.00` |
-| Avg max reward | `1.00` |
-| Eval time (s) | `612.5` |
+Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a local or hub checkpoint.
 
 ---
 
-## Citation
+## Model Details
 
-```bibtex
-@misc{cadene2024lerobot,
-  author = {Cadene, Remi and Alibert, Simon and others},
-  title  = {LeRobot},
-  year   = {2024},
-  url    = {https://github.com/huggingface/lerobot}
-}
-```
+- **License:** apache-2.0

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:c3c88cc528f54dbaf72bb9d93a6b6863c55dbdac62984bc4562e5cab1b184306
 size 1053834112

train_config.json

@@ -199,17 +199,17 @@
         "name": "cosine"
     },
     "eval": {
-        "n_episodes": 2,
-        "batch_size": 2,
+        "n_episodes": 4,
+        "batch_size": 4,
         "use_async_envs": true
     },
     "wandb": {
         "enable": true,
         "disable_artifact": false,
-        "project": "UADP-baselines-tmp",
+        "project": "lerobot",
         "entity": null,
         "notes": null,
-        "run_id": "diffusion_aloha_transfer_cube_seed42",
+        "run_id": "7iqm67o9",
         "mode": null,
         "add_tags": true
     },