Hey @George_Soloupis,
just tested your code suggestion and it indeed leads to the same result.
Sadly i had to learn over the last days that a successful (or rather non-error) conversion of a model does not necessarily mean that one can actually use the result for anything.
If i use the model as followed:
interpreter = tf.lite.Interpreter(model_content=tflite_model)
interpreter.allocate_tensors()

input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()
interpreter.set_tensor(input_details[0]['index'], input_data)

interpreter.invoke()
print("Validation finished successfully.")

then i never get to the final print. The command interpreter.invoke() just randomly exits without any further message or error. I added a verification step to my model before the conversion and can thus confirm that the original model is correctly working.
I also had to learn that since i want to compile the tflite model for a coral-ai TPU i need to add full integer quantization to the tflite-conversion which completly breaks the process.
I’ll probably open a new discussion for that since this question as itself is answered.