Instructions to use denkiwakame/Qwen3.5-2B-LoRA-LAP-UR5e-PyAV with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use denkiwakame/Qwen3.5-2B-LoRA-LAP-UR5e-PyAV with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("denkiwakame/Qwen3.5-2B-LoRA-LAP-UR5e-PyAV", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload model_6k from lap_qwen3_5_2b_fft_ur5e_cluttered_pick_3obj_120_lora as model_final (main)
3ccb535 verified | DATALOADER: | |
| ROBOVERSE: | |
| cfg_opts: IMAGE.crop_img:0.9:IMAGE.img_size:224:IMAGE.cam_list:('3p1','wrist_right1') | |
| cfg_path: libs/RoboVerse/roboverse/configs/ur5e_cluttered_pick_3obj_120.yaml | |
| batch_size: 16 | |
| num_workers: 8 | |
| EXP: | |
| AMP: true | |
| DATASET: roboverse | |
| EXP_ID: lap_qwen3_5_2b_fft_ur5e_cluttered_pick_3obj_120_lora | |
| LOSS: {} | |
| LR_SCHED: none | |
| MODEL: qwen | |
| OPTIMIZER: adamw | |
| SEED: 0 | |
| EXP_EXTRA: | |
| no_test: true | |
| no_track: true | |
| no_val: true | |
| save_at_steps: | |
| - 2000 | |
| - 4000 | |
| - 6000 | |
| - 8000 | |
| save_ckp: 0 | |
| save_last_ckpt: true | |
| test_eval_freq: 1 | |
| val_eval_freq: 1 | |
| LR_SCHED: | |
| lr_clip: 1.0e-08 | |
| lr_decay_factor: 0.5 | |
| lr_patience: 4 | |
| MODEL: | |
| QWEN: | |
| action_mask_aug_per: 0.4 | |
| action_type: original | |
| add_vision_id: true | |
| attention_dropout: 0.0 | |
| enable_thinking: true | |
| grad_checkpoint: false | |
| history: 1 | |
| horizon: 8 | |
| lap_action_is_absolute: true | |
| lap_emit_holds: false | |
| lap_rotation_precision: 1 | |
| lap_sum_decimal: 1f | |
| lora_config: default | |
| lora_rank: 8 | |
| num_bins_actions: 1000 | |
| num_cam: 2 | |
| original_action_dim: 7 | |
| qwen_model_id: Qwen/Qwen3.5-2B | |
| reasoning: true | |
| rgb_img_size: | |
| - 224 | |
| - 224 | |
| rgb_input: true | |
| tiled_rgb_imgs: true | |
| use_flash_attention_2: true | |
| use_lora: true | |
| use_qlora: false | |
| TRAIN: | |
| clip_grad_norm: 0.0 | |
| l2: 1.0e-10 | |
| lr: 1.0e-05 | |
| num_epochs: 100 | |
| num_iters: 10000 | |
| save_iter_ckp: 2500 | |
| WANDB: | |
| enable: true | |
| entity: '' | |
| log_interval: 100 | |
| mode: online | |
| project: vla0 | |
| resume_id: '' | |
| run_name: '' | |
| tags: '' | |