Upload policy weights, train config and readme

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README.md +62 -0
config.json +119 -0
model.safetensors +3 -0
train_config.json +253 -0

README.md ADDED Viewed

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+---
+datasets: lerobot-data-collection/three-folds-dataset-full-11-07
+library_name: lerobot
+license: apache-2.0
+model_name: sarm
+pipeline_tag: robotics
+tags:
+- robotics
+- lerobot
+- sarm
+---
+# Model Card for sarm
+<!-- Provide a quick summary of what the model is/does. -->
+_Model type not recognized — please update this template._
+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 ADDED Viewed

	@@ -0,0 +1,119 @@

+{
+    "type": "sarm",
+    "n_obs_steps": 1,
+    "input_features": {
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+                3
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+    },
+    "device": "cuda",
+    "use_amp": false,
+    "push_to_hub": true,
+    "repo_id": "pepijn223/sarm_dual9",
+    "private": null,
+    "tags": null,
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+    "pretrained_path": null,
+    "image_dim": 512,
+    "text_dim": 512,
+    "num_frames": 9,
+    "frame_gap": 30,
+    "hidden_dim": 768,
+    "num_heads": 12,
+    "num_layers": 8,
+    "max_state_dim": 32,
+    "max_length": 9,
+    "use_temporal_sampler": true,
+    "dual_sparse_dense": true,
+    "num_sparse_stages": 2,
+    "sparse_subtask_names": [
+        "Bring arms up from starting position",
+        "fold the towel (3 folds in total)"
+    ],
+    "sparse_temporal_proportions": [
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+    "dense_subtask_names": [
+        "Bring robot arms up from starting position",
+        "Grab near side and do 1st fold",
+        "Grab side and do 2nd fold",
+        "Grab side and do 3rd fold to finish folding"
+    ],
+    "dense_temporal_proportions": [
+        0.07669543912038806,
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+    "clip_batch_size": 64,
+    "dropout": 0.1,
+    "stage_loss_weight": 1.0,
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+    "image_key": "observation.images.base",
+    "state_key": "observation.state",
+    "dual_inference_mode": "sparse",
+    "normalization_mapping": {
+        "VISUAL": "IDENTITY",
+        "STATE": "MEAN_STD",
+        "LANGUAGE": "IDENTITY",
+        "REWARD": "IDENTITY"
+    }
+}

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train_config.json ADDED Viewed

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+{
+    "dataset": {
+        "repo_id": "lerobot-data-collection/three-folds-dataset-full-11-07",
+        "root": null,
+        "episodes": null,
+        "image_transforms": {
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+}