Instructions to use huangrm/MINT-libero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use huangrm/MINT-libero with LeRobot:
- Notebooks
- Google Colab
- Kaggle
| { | |
| "type": "mint", | |
| "n_obs_steps": 1, | |
| "input_features": { | |
| "observation.images.image": { | |
| "type": "VISUAL", | |
| "shape": [ | |
| 3, | |
| 256, | |
| 256 | |
| ] | |
| }, | |
| "observation.images.image2": { | |
| "type": "VISUAL", | |
| "shape": [ | |
| 3, | |
| 256, | |
| 256 | |
| ] | |
| }, | |
| "observation.state": { | |
| "type": "STATE", | |
| "shape": [ | |
| 8 | |
| ] | |
| } | |
| }, | |
| "output_features": { | |
| "action": { | |
| "type": "ACTION", | |
| "shape": [ | |
| 7 | |
| ] | |
| } | |
| }, | |
| "device": "cuda", | |
| "use_amp": false, | |
| "push_to_hub": true, | |
| "repo_id": "mint", | |
| "private": null, | |
| "tags": null, | |
| "license": null, | |
| "pretrained_path": "lerobot/pi05_base", | |
| "paligemma_variant": "gemma_2b", | |
| "action_expert_variant": "gemma_300m", | |
| "train_expert_only": false, | |
| "dtype": "bfloat16", | |
| "chunk_size": 16, | |
| "n_action_steps": 1, | |
| "label_smooth": 0.0, | |
| "max_state_dim": 32, | |
| "max_action_dim": 7, | |
| "codebook_size": 512, | |
| "codebook_dim": 32, | |
| "ch": 48, | |
| "ch_mult": [ | |
| 2, | |
| 4, | |
| 8 | |
| ], | |
| "patch_nums": [ | |
| 1, | |
| 2, | |
| 4 | |
| ], | |
| "znorm": true, | |
| "quant_conv_ks": 3, | |
| "quant_resi": 0.5, | |
| "share_quant_resi": 0, | |
| "patchwise": { | |
| "enable": true, | |
| "d_embed": 8, | |
| "grouped_depth": 2, | |
| "norm": "layer" | |
| }, | |
| "vqvae_name_or_path": "", | |
| "image_resolution": [ | |
| 224, | |
| 224 | |
| ], | |
| "empty_cameras": 0, | |
| "tokenizer_max_length": 200, | |
| "normalization_mapping": { | |
| "VISUAL": "IDENTITY", | |
| "STATE": "QUANTILES", | |
| "ACTION": "IDENTITY" | |
| }, | |
| "gradient_checkpointing": true, | |
| "compile_model": false, | |
| "compile_mode": "max-autotune", | |
| "optimizer_lr": 0.00025, | |
| "optimizer_betas": [ | |
| 0.9, | |
| 0.95 | |
| ], | |
| "optimizer_eps": 1e-08, | |
| "optimizer_weight_decay": 0.01, | |
| "optimizer_grad_clip_norm": 1.0, | |
| "scheduler_warmup_steps": 1000, | |
| "scheduler_decay_steps": 30000, | |
| "scheduler_decay_lr": 2.5e-05 | |
| } |