i have created a ML project

import pandas as pd
import numpy as np
import tensorflow as tf
from sklearn.preprocessing import LabelEncoder
from keras.utils import to_categorical

df = pd.read_csv('iris.data')

X = df.iloc[:, :4].values
y = df.iloc[:, 4].values

le = LabelEncoder()

y = le.fit_transform(y)
y = to_categorical(y)

from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential

model = Sequential()

model.add(Dense(64, activation='relu', input_shape=[4]))
model.add(Dense(64))
model.add(Dense(3, activation='softmax'))

model.compile(optimizer='sgd', loss='categorical_crossentropy',
metrics=['acc'])

model.fit(X, y, epochs=200)

from tensorflow import lite
converter = lite.TFLiteConverter.from_keras_model(model)

tfmodel = converter.convert()

open('iris.tflite', 'wb').write(tfmodel)