File size: 690 Bytes
1976483 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | import tensorflow as tf
import os
print("Loading model...")
model = tf.keras.models.load_model("sentiment_model.h5")
# Convert with dynamic batch size (None instead of 256)
@tf.function(input_signature=[tf.TensorSpec(shape=[None, 100], dtype=tf.float32)])
def predict(x):
return model(x)
converter = tf.lite.TFLiteConverter.from_concrete_functions(
[predict.get_concrete_function()]
)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
tflite_model = converter.convert()
with open("sentiment_model.tflite", "wb") as f:
f.write(tflite_model)
print(f"Size: {os.path.getsize('sentiment_model.tflite') / 1024 / 1024:.1f} MB")
print("Done! Dynamic batch size model created.")
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