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Upload and train machine learning models on a remote server.

Project description

CitadelML

Upload and train machine learning models on a remote server.

Setup

pip install citadelml

Quick use

Create a tensorflow model, and then send it to the server.

from citadelml import upload_model
import tensorflow as tf

model = tf.keras.models.Sequential([
    tf.keras.layers.experimental.preprocessing.Rescaling(1./255),
    tf.keras.layers.Flatten(input_shape=(28, 28)),
    tf.keras.layers.Dense(128, activation='relu'),
    tf.keras.layers.Dropout(0.2),
    tf.keras.layers.Dense(10)
])

upload_model(
    server='http://localhost:5000',
    dataset='example_dataset',
    username='usernameGoesHere',
    password='passwordGoesHere',
    model=model,
    loss_function='tf.keras.losses.SparseCategoricalCrossentropy',
    optimizer='adam',
    n_epochs=5,
    seed=12345,
    split=0.2,
    batch_size=32,
    save_training_results=False
)

Project details


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  • Size: 3.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/51.3.3 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.8.0

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