Instructions to use Haongchen/MemoryVLA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Piper
How to use Haongchen/MemoryVLA with Piper:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Add runtime aliases and CogACT base metadata
Browse files- config.json +63 -0
config.json
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{
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"action_dim": 7,
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"action_model_type": "DiT-L",
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"consolidate_type": "tome",
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"data_root_dir": "/training-results/haodong/Real/memoryvla_rlds",
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"dataloader_type": "stream",
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"ema_decay": 0.999,
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"fusion_type": "gate",
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"future_action_window_size": 15,
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"group_size": 16,
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"hf_token": "HF_TOKEN",
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"image_aug": false,
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"image_aug_mode": "spatial",
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"is_resume": false,
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"load_all_data_for_training": true,
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"mem_length": 256,
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"per_token_size": 256,
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"pretrained_checkpoint": "/training-results/haodong/MemoryVLA/code/pretrained/CogACT-Large/checkpoints/CogACT-Large.pt",
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"repeated_diffusion_steps": 4,
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"resume_epoch": 0,
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"resume_step": 0,
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"retain_optimizer_checkpoints": 2,
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"retrieval_layers": 2,
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"run_id": "piper-color-sorting-frozen16-ema-real21-20260823-053817",
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"run_id_note": null,
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"run_root_dir": "/training-results/haodong/MemoryVLA/runs/piper-color-sorting",
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"save_interval": 2000,
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"save_on_terminate": true,
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"seed": 42,
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"trackers": [
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"jsonl",
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"wandb"
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],
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"update_fused": false,
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"use_ema": true,
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"use_timestep_pe": true,
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"vla": {
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"base_vlm": "prism-dinosiglip-224px+7b",
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"data_mix": "custom_finetuning",
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"enable_gradient_checkpointing": true,
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"enable_mixed_precision_training": true,
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"epochs": 100,
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"expected_world_size": 16,
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"freeze_llm_backbone": true,
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"freeze_vision_backbone": true,
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"global_batch_size": 32,
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"learning_rate": 2e-05,
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"lr_scheduler_type": "linear-warmup+cosine-decay",
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"max_grad_norm": 1.0,
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"max_steps": 20000,
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"per_device_batch_size": 2,
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"reduce_in_full_precision": true,
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"shuffle_buffer_size": 64,
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"train_strategy": "fsdp-full-shard",
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"type": "prism-dinosiglip-224px+oxe+diffusion",
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"unfreeze_last_llm_layer": false,
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"vla_id": "prism-dinosiglip-224px+oxe+diffusion",
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"warmup_ratio": 0.03,
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"weight_decay": 0.0
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},
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"wandb_entity": "spikingtransformer",
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"wandb_project": "Memory World Model"
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}
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