Instructions to use keras/swin_tiny_patch4_window7_224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/swin_tiny_patch4_window7_224 with KerasHub:
import keras_hub import keras # Load ImageClassifier model image_classifier = keras_hub.models.ImageClassifier.from_preset( "hf://keras/swin_tiny_patch4_window7_224", num_classes=2, ) # Fine-tune image_classifier.fit( x=keras.random.randint((32, 64, 64, 3), 0, 256), y=keras.random.randint((32, 1), 0, 2), ) # Classify image image_classifier.predict(keras.random.randint((1, 64, 64, 3), 0, 256))import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/swin_tiny_patch4_window7_224") - Keras
How to use keras/swin_tiny_patch4_window7_224 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras/swin_tiny_patch4_window7_224") - Notebooks
- Google Colab
- Kaggle
File size: 4,206 Bytes
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"module": "keras_hub.src.models.swin_transformer.swin_transformer_image_classifier",
"class_name": "SwinTransformerImageClassifier",
"config": {
"backbone": {
"module": "keras_hub.src.models.swin_transformer.swin_transformer_backbone",
"class_name": "SwinTransformerBackbone",
"config": {
"name": "swin_transformer_backbone",
"trainable": true,
"dtype": {
"module": "keras",
"class_name": "DTypePolicy",
"config": {
"name": "float32"
},
"registered_name": null
},
"image_shape": [
224,
224,
3
],
"patch_size": 4,
"embed_dim": 96,
"depths": [
2,
2,
6,
2
],
"num_heads": [
3,
6,
12,
24
],
"window_size": 7,
"mlp_ratio": 4.0,
"qkv_bias": true,
"dropout_rate": 0.0,
"attention_dropout": 0.0,
"drop_path": 0.1,
"patch_norm": true,
"data_format": "channels_last"
},
"registered_name": "keras_hub>SwinTransformerBackbone"
},
"preprocessor": {
"module": "keras_hub.src.models.swin_transformer.swin_transformer_image_classifier_preprocessor",
"class_name": "SwinTransformerImageClassifierPreprocessor",
"config": {
"name": "swin_transformer_image_classifier_preprocessor",
"trainable": true,
"dtype": {
"module": "keras",
"class_name": "DTypePolicy",
"config": {
"name": "float32"
},
"registered_name": null
},
"image_converter": {
"module": "keras_hub.src.models.swin_transformer.swin_transformer_image_converter",
"class_name": "SwinTransformerImageConverter",
"config": {
"name": "swin_transformer_image_converter",
"trainable": true,
"dtype": {
"module": "keras",
"class_name": "DTypePolicy",
"config": {
"name": "float32"
},
"registered_name": null
},
"image_size": [
224,
224
],
"scale": [
0.017124753831663668,
0.01750700280112045,
0.017429193899782133
],
"offset": [
-2.1179039301310043,
-2.0357142857142856,
-1.8044444444444445
],
"interpolation": "bicubic",
"antialias": true,
"crop_to_aspect_ratio": false,
"pad_to_aspect_ratio": false,
"bounding_box_format": "yxyx"
},
"registered_name": "keras_hub>SwinTransformerImageConverter"
},
"config_file": "preprocessor.json"
},
"registered_name": "keras_hub>SwinTransformerImageClassifierPreprocessor"
},
"name": "swin_transformer_image_classifier",
"num_classes": 1000,
"pooling": "gap",
"activation": null,
"dropout": 0.0
},
"registered_name": "keras_hub>SwinTransformerImageClassifier"
} |