Instructions to use Synaptics/MobileNetV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Synaptics/MobileNetV2 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Synaptics/MobileNetV2") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
language:
- en
library_name: keras
tags:
- tests
- tf_model_zoo
MobileNetV2
This model - MobileNetV2 is generated from tf.keras.applications
using tf_model_generator.py.
The dataset for int8 quantization is done using random data.
Available formats: int16, int8, float32, float16
The kaggle.tflite model is the original quantized model
published by Google. This model uses v1 tflite quantization.