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YOLOv8-16bit/docs/reference/nn/tasks.md

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description keywords
Learn how to work with Ultralytics YOLO Detection, Segmentation & Classification Models, load weights and parse models in PyTorch. neural network, deep learning, computer vision, object detection, image segmentation, image classification, model ensemble, PyTorch

BaseModel

::: ultralytics.nn.tasks.BaseModel



DetectionModel

::: ultralytics.nn.tasks.DetectionModel



SegmentationModel

::: ultralytics.nn.tasks.SegmentationModel



PoseModel

::: ultralytics.nn.tasks.PoseModel



ClassificationModel

::: ultralytics.nn.tasks.ClassificationModel



RTDETRDetectionModel

::: ultralytics.nn.tasks.RTDETRDetectionModel



Ensemble

::: ultralytics.nn.tasks.Ensemble



torch_safe_load

::: ultralytics.nn.tasks.torch_safe_load



attempt_load_weights

::: ultralytics.nn.tasks.attempt_load_weights



attempt_load_one_weight

::: ultralytics.nn.tasks.attempt_load_one_weight



parse_model

::: ultralytics.nn.tasks.parse_model



yaml_model_load

::: ultralytics.nn.tasks.yaml_model_load



guess_model_scale

::: ultralytics.nn.tasks.guess_model_scale



guess_model_task

::: ultralytics.nn.tasks.guess_model_task