Image Classification
Keras
LiteRT
TF-Keras
Safetensors
English
efficientnetv2-s
efficientnetv2
fgic
transfer-learning
gem-pooling
focal-loss
swa
grad-cam
calibration
temperature-scaling
computer-vision
tensorflow.js
Eval Results (legacy)
Instructions to use 0xgr3y/Arch-Building-Image-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use 0xgr3y/Arch-Building-Image-Classification with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://0xgr3y/Arch-Building-Image-Classification") - Notebooks
- Google Colab
- Kaggle
Upload model_benchmark.json with huggingface_hub
Browse files- model_benchmark.json +21 -21
model_benchmark.json
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{
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"model_file": "fine_tuning_swa.keras",
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"architecture": "EfficientNetV2-S+Conv2D(256)+BN+MaxPool2D+GeMPooling+Dense(256)+BN+Dropout(0.4)+Dense(8,softmax)",
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