# ```python
# import torch
# from sam2.build_sam import build_sam2_video_predictor

# checkpoint = "./checkpoints/sam2.1_hiera_large.pt"
# model_cfg = "configs/sam2.1/sam2.1_hiera_l.yaml"
# predictor = build_sam2_video_predictor(model_cfg, checkpoint)

# with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16):
#     state = predictor.init_state(<your_video>)

#     # add new prompts and instantly get the output on the same frame
#     frame_idx, object_ids, masks = predictor.add_new_points_or_box(state, <your_prompts>):

#     # propagate the prompts to get masklets throughout the video
#     for frame_idx, object_ids, masks in predictor.propagate_in_video(state):
#         ...
# ```