{
  "id": "tanreinama/blending-se-resnext50-and-convnextv2",
  "id_no": 32908424,
  "title": "Blending SE-ResNeXt50 and ConvNextV2",
  "code_file": "blending-se-resnext50-and-convnextv2.ipynb",
  "language": "python",
  "kernel_type": "notebook",
  "is_private": false,
  "enable_gpu": true,
  "enable_tpu": false,
  "enable_internet": false,
  "keywords": [
    "gpu"
  ],
  "dataset_sources": [
    "markwijkhuizen/keras-cv-attention-models",
    "christofhenkel/nvidia-dali-nightly-cuda110-1230dev",
    "christofhenkel/rsna-bc-pip-requirements",
    "markwijkhuizen/rsna-efficientnetv2-training-tensorflow-tpu-ds",
    "christofhenkel/rsna-seresnext50-5fold"
  ],
  "kernel_sources": [],
  "competition_sources": [
    "rsna-breast-cancer-detection"
  ],
  "model_sources": [],
  "docker_image": "gcr.io/kaggle-private-byod/python@sha256:c75700eb2ebadc2512e3da6d394c0bb3e0fc8c8cd3598e6b3f94c6873e7a5dca",
  "machine_shape": "Gpu"
}