Upload policy
Browse files- README.md +64 -0
- config.json +94 -0
- model.safetensors +3 -0
README.md
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---
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base_model: lerobot/smolvla_base
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datasets:
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- imstevenpmwork/thanos_picking_power_gem_1749731584242992
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library_name: lerobot
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license: apache-2.0
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model_name: smolvla
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pipeline_tag: robotics
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tags:
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- robotics
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- smolvla
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model_summary: '[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact,
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efficient vision-language-action model that achieves competitive performance at
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reduced computational costs and can be deployed on consumer-grade hardware.'
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---
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# Model Card for smolvla
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<!-- Provide a quick summary of what the model is/does. -->
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[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.
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This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
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See the full documentation at [LeRobot Docs](https://huggingface.co/docs/lerobot/index).
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---
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## How to Get Started with the Model
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For a complete walkthrough, see the [training guide](https://huggingface.co/docs/lerobot/il_robots#train-a-policy).
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Below is the short version on how to train and run inference/eval:
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### 1 Train from scratch
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```bash
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python lerobot/scripts/train.py \
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--dataset.repo_id=${HF_USER}/<dataset> \
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--policy.type=act \
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--output_dir=outputs/train/<desired_policy_repo_id> \
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--job_name=lerobot_training \
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--policy.device=cuda \
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--policy.repo_id=${HF_USER}/<desired_policy_repo_id>
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--wandb.enable=true
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```
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*Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`.*
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### 2 Evaluate the policy
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```bash
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python -m lerobot.record \
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--robot.type=so100_follower \
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--dataset.repo_id=<hf_user>/eval_<dataset> \
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--policy.path=<hf_user>/<desired_policy_repo_id> \
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--episodes=10
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```
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Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a local or hub checkpoint.
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---
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## Model Details
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* **License:** apache-2.0
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config.json
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{
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"type": "smolvla",
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"n_obs_steps": 1,
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"normalization_mapping": {
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"VISUAL": "IDENTITY",
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"STATE": "MEAN_STD",
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"ACTION": "MEAN_STD"
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},
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"input_features": {
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"observation.state": {
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"type": "STATE",
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"shape": [
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6
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]
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},
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"observation.images.front": {
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"type": "VISUAL",
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"shape": [
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3,
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480,
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640
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]
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},
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"observation.images.eagle": {
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"type": "VISUAL",
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"shape": [
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3,
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480,
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640
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]
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},
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"observation.images.glove": {
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"type": "VISUAL",
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"shape": [
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3,
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480,
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640
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]
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}
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},
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"output_features": {
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"action": {
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"type": "ACTION",
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"shape": [
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6
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]
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}
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},
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"device": "mps",
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"use_amp": false,
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"push_to_hub": true,
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"repo_id": "pepijn223/my_policy21",
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"dataset_repo_id": "imstevenpmwork/thanos_picking_power_gem_1749731584242992",
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"chunk_size": 50,
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"n_action_steps": 50,
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"max_state_dim": 32,
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"max_action_dim": 32,
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"resize_imgs_with_padding": [
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512,
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512
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],
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"empty_cameras": 0,
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"adapt_to_pi_aloha": false,
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"use_delta_joint_actions_aloha": false,
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"tokenizer_max_length": 48,
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"num_steps": 10,
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"use_cache": true,
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"freeze_vision_encoder": true,
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"train_expert_only": true,
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"train_state_proj": true,
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"optimizer_lr": 0.0001,
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"optimizer_betas": [
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0.9,
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0.95
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],
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"optimizer_eps": 1e-08,
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"optimizer_weight_decay": 1e-10,
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"optimizer_grad_clip_norm": 10,
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"scheduler_warmup_steps": 1000,
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"scheduler_decay_steps": 30000,
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"scheduler_decay_lr": 2.5e-06,
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"vlm_model_name": "HuggingFaceTB/SmolVLM2-500M-Video-Instruct",
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"load_vlm_weights": false,
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"add_image_special_tokens": false,
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"attention_mode": "cross_attn",
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"prefix_length": -1,
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"pad_language_to": "longest",
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"num_expert_layers": -1,
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"num_vlm_layers": 16,
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"self_attn_every_n_layers": 2,
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"expert_width_multiplier": 0.75,
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"min_period": 0.004,
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"max_period": 4.0
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:67410f443d0747f4f3360792aa2eff6931f8b946cb0b7cbb2a8035cac3de1308
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size 1197790016
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