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import tensorflow as tf
#load required libraries and functions such as load_model etc
model_path = './example.h5' #path to your model

tf_model = tf.keras.models.load_model( model_path )
converter = tf.lite.TFLiteConverter.from_keras_model( tf_model )

tf_lite_model = converter.convert()

open( 'facenet.tflite' , 'wb' ).write( tf_lite_model )

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#pip install opendatasets
#this will download the datasets into the specified folder / Google Drive


#pass the kaggle dataset URL string as an argument to od.download() function
import opendatasets as od
od.download("https://www.kaggle.com/datasets/jangedoo/utkface-new")

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'''
=> df
  Location  Parameter
0        A         10
1        A         20
2        B         14
3        B         16
4        C         15
5        C          9
6        C          6

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# Import necessary libraries
# Need to install requests and openai using PIP
# Go to your openai page and get your API from there and update below in the code.

import openai
import requests
import os

# Set the OpenAI API key
openai.api_key = "YOUR_API_KEY"

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from sentence_transformers import SentenceTransformer, util
import time

model = SentenceTransformer("all-MiniLM-L6-v2")

# Two lists of sentences
sentences1 = [
    "I want to know about financial advice about car loan.",
]

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import requests
import base64

# https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/sdxl/api
API_KEY = "GET API KEY FROM NVIDIA PLAYGROUND FROM ABOVE LINK IN COMMENT"

invoke_url = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/functions/89848fb8-549f-41bb-88cb-95d6597044a4"
fetch_url_format = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/status/"

headers = {