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Instantiates the ConvNeXtTiny architecture.
tf.keras.applications.convnext.ConvNeXtTiny(
model_name='convnext_tiny',
include_top=True,
include_preprocessing=True,
weights='imagenet',
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
classifier_activation='softmax'
)
References | |
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For image classification use cases, see this page for detailed examples. For transfer learning use cases, make sure to read the guide to transfer learning & fine-tuning.
The base
, large
, and xlarge
models were first pre-trained on the
ImageNet-21k dataset and then fine-tuned on the ImageNet-1k dataset. The
pre-trained parameters of the models were assembled from the
official repository. To get a
sense of how these parameters were converted to Keras compatible parameters,
please refer to
this repository.
When calling the summary()
method after instantiating a ConvNeXt model,
prefer setting the expand_nested
argument summary()
to True
to better
investigate the instantiated model.
Args | |
---|---|
include_top
|
Whether to include the fully-connected layer at the top of the network. Defaults to True. |
weights
|
One of None (random initialization),
"imagenet" (pre-training on ImageNet-1k), or the path to the weights
file to be loaded. Defaults to "imagenet" .
|
input_tensor
|
Optional Keras tensor
(i.e. output of layers.Input() )
to use as image input for the model.
|
input_shape
|
Optional shape tuple, only to be specified
if include_top is False.
It should have exactly 3 inputs channels.
|
pooling
|
Optional pooling mode for feature extraction
when include_top is False . Defaults to None.
|
classes
|
Optional number of classes to classify images
into, only to be specified if include_top is True, and
if no weights argument is specified. Defaults to 1000 (number of
ImageNet classes).
|
classifier_activation
|
A str or callable. The activation function to use
on the "top" layer. Ignored unless include_top=True . Set
classifier_activation=None to return the logits of the "top" layer.
Defaults to "softmax" .
When loading pretrained weights, classifier_activation can only
be None or "softmax" .
|
Returns | |
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A keras.Model instance.
|