[python] Keras, how do I predict after I trained a model?

You can just "call" your model with an array of the correct shape:

model(np.array([[6.7, 3.3, 5.7, 2.5]]))

Full example:

from sklearn.datasets import load_iris
from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential
import numpy as np

X, y = load_iris(return_X_y=True)

model = Sequential([
    Dense(16, activation='relu'),
    Dense(32, activation='relu'),
    Dense(1)])

model.compile(loss='mean_absolute_error', optimizer='adam')

history = model.fit(X, y, epochs=10, verbose=0)

print(model(np.array([[6.7, 3.3, 5.7, 2.5]])))
<tf.Tensor: shape=(1, 1), dtype=float64, numpy=array([[1.92517677]])>

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