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Upload policy weights, train config and readme

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  1. README.md +66 -0
  2. config.json +69 -0
  3. model.safetensors +3 -0
  4. train_config.json +181 -0
README.md ADDED
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+ ---
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+ datasets:
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+ - shuohsuan/grasp0
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+ - shuohsuan/grasp1
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+ - shuohsuan/grasp2
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+ - shuohsuan/grasp3
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+ library_name: lerobot
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+ license: apache-2.0
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+ model_name: act
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+ pipeline_tag: robotics
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+ tags:
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+ - act
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+ - lerobot
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+ - robotics
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+ ---
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+
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+ # Model Card for act
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+ [Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates.
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+
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+
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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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+ ---
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+
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+ ## How to Get Started with the Model
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+
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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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+
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+ ### Train from scratch
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+
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+ ```bash
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+ python -m lerobot.scripts.train \
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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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+
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+ *Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`.*
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+
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+ ### Evaluate the policy/run inference
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+
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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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+
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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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+ ---
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+
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+ ## Model Details
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+
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+ * **License:** apache-2.0
config.json ADDED
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+ {
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+ "type": "act",
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+ "n_obs_steps": 1,
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+ "normalization_mapping": {
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+ "VISUAL": "MEAN_STD",
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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.side": {
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+ "type": "VISUAL",
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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": "cuda",
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+ "use_amp": false,
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+ "push_to_hub": true,
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+ "repo_id": "shuohsuan/act_grasp0123",
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+ "private": null,
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+ "tags": null,
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+ "license": null,
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+ "chunk_size": 100,
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+ "n_action_steps": 100,
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+ "vision_backbone": "resnet18",
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+ "pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
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+ "replace_final_stride_with_dilation": false,
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+ "pre_norm": false,
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+ "dim_model": 512,
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+ "n_heads": 8,
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+ "dim_feedforward": 3200,
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+ "feedforward_activation": "relu",
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+ "n_encoder_layers": 4,
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+ "n_decoder_layers": 1,
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+ "use_vae": true,
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+ "latent_dim": 32,
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+ "n_vae_encoder_layers": 4,
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+ "temporal_ensemble_coeff": null,
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+ "dropout": 0.1,
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+ "kl_weight": 10.0,
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+ "optimizer_lr": 1e-05,
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+ "optimizer_weight_decay": 0.0001,
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+ "optimizer_lr_backbone": 1e-05
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+ }
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train_config.json ADDED
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+ {
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+ "dataset": {
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+ "repo_id": [
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+ "shuohsuan/grasp0",
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+ "shuohsuan/grasp1",
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+ "shuohsuan/grasp2",
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+ "shuohsuan/grasp3"
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+ "video_backend": "torchcodec"
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+ "env": null,
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+ "policy": {
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+ "type": "act",
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+ "n_obs_steps": 1,
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+ "normalization_mapping": {
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+ "VISUAL": "MEAN_STD",
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+ "STATE": "MEAN_STD",
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+ "ACTION": "MEAN_STD"
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+ "replace_final_stride_with_dilation": false,
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+ "pre_norm": false,
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+ "dim_model": 512,
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+ "n_heads": 8,
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+ "dim_feedforward": 3200,
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+ "save_checkpoint": true,
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+ }
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+ }