keras / efficientnet2_rw_t_ra2_imagenet

huggingface.co
Total runs: 9
24-hour runs: 0
7-day runs: 3
30-day runs: 5
Model's Last Updated: June 17 2025

Introduction of efficientnet2_rw_t_ra2_imagenet

Model Details of efficientnet2_rw_t_ra2_imagenet

This is a EfficientNet model uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends. This model is related to a ImageClassifier task.

Model config:

  • name: efficient_net_backbone
  • trainable: True
  • stackwise_width_coefficients: [0.8, 0.8, 0.8, 0.8, 0.8, 0.8]
  • stackwise_depth_coefficients: [0.9, 0.9, 0.9, 0.9, 0.9, 0.9]
  • dropout: 0
  • depth_divisor: 8
  • min_depth: None
  • activation: silu
  • input_shape: [None, None, 3]
  • stackwise_kernel_sizes: [3, 3, 3, 3, 3, 3]
  • stackwise_num_repeats: [2, 4, 4, 6, 9, 15]
  • stackwise_input_filters: [24, 24, 48, 64, 128, 160]
  • stackwise_output_filters: [24, 48, 64, 128, 160, 256]
  • stackwise_expansion_ratios: [1, 4, 4, 4, 6, 6]
  • stackwise_squeeze_and_excite_ratios: [0, 0, 0, 0.25, 0.25, 0.25]
  • stackwise_strides: [1, 2, 2, 2, 1, 2]
  • stackwise_block_types: ['cba', 'fused', 'fused', 'unfused', 'unfused', 'unfused']
  • stackwise_force_input_filters: [0, 0, 0, 0, 0, 0]
  • include_stem_padding: True
  • use_depth_divisor_as_min_depth: True
  • cap_round_filter_decrease: True
  • stem_conv_padding: valid
  • batch_norm_momentum: 0.9
  • batch_norm_epsilon: 1e-05
  • projection_activation: None

This model card has been generated automatically and should be completed by the model author. See Model Cards documentation for more information.

Runs of keras efficientnet2_rw_t_ra2_imagenet on huggingface.co

9
Total runs
0
24-hour runs
0
3-day runs
3
7-day runs
5
30-day runs

More Information About efficientnet2_rw_t_ra2_imagenet huggingface.co Model

efficientnet2_rw_t_ra2_imagenet huggingface.co

efficientnet2_rw_t_ra2_imagenet huggingface.co is an AI model on huggingface.co that provides efficientnet2_rw_t_ra2_imagenet's model effect (), which can be used instantly with this keras efficientnet2_rw_t_ra2_imagenet model. huggingface.co supports a free trial of the efficientnet2_rw_t_ra2_imagenet model, and also provides paid use of the efficientnet2_rw_t_ra2_imagenet. Support call efficientnet2_rw_t_ra2_imagenet model through api, including Node.js, Python, http.

efficientnet2_rw_t_ra2_imagenet huggingface.co Url

https://huggingface.co/keras/efficientnet2_rw_t_ra2_imagenet

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keras efficientnet2_rw_t_ra2_imagenet online free url in huggingface.co:

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efficientnet2_rw_t_ra2_imagenet install

efficientnet2_rw_t_ra2_imagenet is an open source model from GitHub that offers a free installation service, and any user can find efficientnet2_rw_t_ra2_imagenet on GitHub to install. At the same time, huggingface.co provides the effect of efficientnet2_rw_t_ra2_imagenet install, users can directly use efficientnet2_rw_t_ra2_imagenet installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

efficientnet2_rw_t_ra2_imagenet install url in huggingface.co:

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efficientnet2_rw_t_ra2_imagenet huggingface.co Url

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