Upload policy weights, train config and readme

README.md

@@ -0,0 +1,63 @@
+---
+base_model: lerobot/smolvla_base
+datasets: TANAY779/SmolVLA_Stacking
+library_name: lerobot
+license: apache-2.0
+model_name: smolvla
+pipeline_tag: robotics
+tags:
+- lerobot
+- robotics
+- smolvla
+---
+
+# Model Card for smolvla
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
+
+
+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

@@ -57,7 +57,7 @@
     "private": null,
     "tags": null,
     "license": null,
-    "pretrained_path": "lerobot/smolvla_base",
+    "pretrained_path": "outputs/train/SmolVLA_Stacking_3_Cubes/checkpoints/012000/pretrained_model",
     "chunk_size": 50,
     "n_action_steps": 50,
     "normalization_mapping": {

model.safetensors

@@ -1,3 +1,3 @@
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 size 906712520

train_config.json

@@ -140,7 +140,7 @@
         "private": null,
         "tags": null,
         "license": null,
-        "pretrained_path": "lerobot/smolvla_base",
+        "pretrained_path": "outputs/train/SmolVLA_Stacking_3_Cubes/checkpoints/012000/pretrained_model",
         "chunk_size": 50,
         "n_action_steps": 50,
         "normalization_mapping": {
@@ -192,7 +192,7 @@
     },
     "output_dir": "outputs/train/SmolVLA_Stacking_3_Cubes",
     "job_name": "SmolVLA_Stacking_3_Cubes",
-    "resume": false,
+    "resume": true,
     "seed": 1000,
     "cudnn_deterministic": false,
     "num_workers": 4,
@@ -249,5 +249,5 @@
         "observation.images.overhead": "observation.images.camera1",
         "observation.images.wrist": "observation.images.camera2"
     },
-    "checkpoint_path": null
+    "checkpoint_path": "outputs/train/SmolVLA_Stacking_3_Cubes/checkpoints/012000"
 }