wehub-resource-sync
184 lines
10 KiB
Plaintext
184 lines
10 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "5DKDTnMGHTGn"
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},
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"source": [
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"# If you are using Colab for free, we highly recommend you activate the T4 GPU\n",
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"# hardware accelerator. Our models are designed to run with at least 16GB\n",
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"# of RAM, activating T4 will grant the notebook 16GB of GDDR6 RAM as opposed\n",
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"# to the ~13GB Colab gives automatically.\n",
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"# To activate T4:\n",
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"# 1. click on the \"Runtime\" tab\n",
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"# 2. click on \"Change runtime type\"\n",
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"# 3. select T4 GPU under Hardware Accelerator\n",
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"# NOTE: there is a weekly usage limit on using T4 for free"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "aBE4SLY5LYiq"
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},
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"source": [
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"##This example aims to show how to run multiple specific queries on text using our slim extract tool, and ouput it as a dictionary"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "oanCf6Dn8UlA",
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"outputId": "84e6207b-40bb-47b6-d756-ae6ead743bc1"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: llmware in /usr/local/lib/python3.10/dist-packages (0.3.0)\n",
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"Requirement already satisfied: boto3>=1.24.53 in /usr/local/lib/python3.10/dist-packages (from llmware) (1.34.129)\n",
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"Requirement already satisfied: huggingface-hub>=0.19.4 in /usr/local/lib/python3.10/dist-packages (from llmware) (0.23.3)\n",
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"Requirement already satisfied: numpy>=1.23.2 in /usr/local/lib/python3.10/dist-packages (from llmware) (1.25.2)\n",
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"Requirement already satisfied: psycopg-binary==3.1.17 in /usr/local/lib/python3.10/dist-packages (from llmware) (3.1.17)\n",
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"Requirement already satisfied: psycopg==3.1.17 in /usr/local/lib/python3.10/dist-packages (from llmware) (3.1.17)\n",
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"Requirement already satisfied: pgvector==0.2.4 in /usr/local/lib/python3.10/dist-packages (from llmware) (0.2.4)\n",
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"Requirement already satisfied: colorama==0.4.6 in /usr/local/lib/python3.10/dist-packages (from llmware) (0.4.6)\n",
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"Requirement already satisfied: librosa>=0.10.0 in /usr/local/lib/python3.10/dist-packages (from llmware) (0.10.2.post1)\n",
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"Requirement already satisfied: typing-extensions>=4.1 in /usr/local/lib/python3.10/dist-packages (from psycopg==3.1.17->llmware) (4.12.2)\n",
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"Requirement already satisfied: botocore<1.35.0,>=1.34.129 in /usr/local/lib/python3.10/dist-packages (from boto3>=1.24.53->llmware) (1.34.129)\n",
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"Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from boto3>=1.24.53->llmware) (1.0.1)\n",
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"Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /usr/local/lib/python3.10/dist-packages (from boto3>=1.24.53->llmware) (0.10.1)\n",
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"Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.19.4->llmware) (3.14.0)\n",
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"Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.19.4->llmware) (6.0.1)\n",
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"Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.19.4->llmware) (2.31.0)\n",
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"Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.19.4->llmware) (4.66.4)\n",
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"Requirement already satisfied: scipy>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from librosa>=0.10.0->llmware) (1.11.4)\n",
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"Requirement already satisfied: scikit-learn>=0.20.0 in /usr/local/lib/python3.10/dist-packages (from librosa>=0.10.0->llmware) (1.2.2)\n",
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"Requirement already satisfied: joblib>=0.14 in /usr/local/lib/python3.10/dist-packages (from librosa>=0.10.0->llmware) (1.4.2)\n",
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"Requirement already satisfied: decorator>=4.3.0 in /usr/local/lib/python3.10/dist-packages (from librosa>=0.10.0->llmware) (4.4.2)\n",
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"Requirement already satisfied: pooch>=1.1 in /usr/local/lib/python3.10/dist-packages (from librosa>=0.10.0->llmware) (1.8.2)\n",
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"Requirement already satisfied: soxr>=0.3.2 in /usr/local/lib/python3.10/dist-packages (from librosa>=0.10.0->llmware) (0.3.7)\n",
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"Requirement already satisfied: lazy-loader>=0.1 in /usr/local/lib/python3.10/dist-packages (from librosa>=0.10.0->llmware) (0.4)\n",
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"Requirement already satisfied: msgpack>=1.0 in /usr/local/lib/python3.10/dist-packages (from librosa>=0.10.0->llmware) (1.0.8)\n",
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"Requirement already satisfied: dnspython<3.0.0,>=1.16.0 in /usr/local/lib/python3.10/dist-packages (from pymongo>=4.7.0->llmware) (2.6.1)\n",
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"Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /usr/local/lib/python3.10/dist-packages (from botocore<1.35.0,>=1.34.129->boto3>=1.24.53->llmware) (2.8.2)\n",
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"Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /usr/local/lib/python3.10/dist-packages (from botocore<1.35.0,>=1.34.129->boto3>=1.24.53->llmware) (2.0.7)\n",
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"Requirement already satisfied: llvmlite<0.42,>=0.41.0dev0 in /usr/local/lib/python3.10/dist-packages (from numba>=0.51.0->librosa>=0.10.0->llmware) (0.41.1)\n",
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"Requirement already satisfied: platformdirs>=2.5.0 in /usr/local/lib/python3.10/dist-packages (from pooch>=1.1->librosa>=0.10.0->llmware) (4.2.2)\n",
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"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.19.4->llmware) (3.7)\n",
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"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.19.4->llmware) (2024.6.2)\n",
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"Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.20.0->librosa>=0.10.0->llmware) (3.5.0)\n",
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"Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.10/dist-packages (from soundfile>=0.12.1->librosa>=0.10.0->llmware) (1.16.0)\n",
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"Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.0->soundfile>=0.12.1->librosa>=0.10.0->llmware) (2.22)\n",
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"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.35.0,>=1.34.129->boto3>=1.24.53->llmware) (1.16.0)\n"
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]
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}
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],
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"source": [
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"!pip install llmware\n",
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"from llmware.models import ModelCatalog\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "erpOjVoUGZPU"
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},
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"source": [
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"To add more strings to analyze, add them to Text_to_analyze.\n",
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"To add more queries, add them to queries_list.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {
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"id": "Ls6GHIEqF1uq"
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},
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"outputs": [],
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"source": [
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"Text_to_analyze = [\"I am John Doe, I visited Peter, a therapist in the year 2019. I travelled to NYC for around 5 therapy sessions, I was advised to be more outgoing.\"]\n",
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"queries_list = [\"consultant specialty\", \"Consultant name\", \"Consultant location\", \"Consultant Advice\"]\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "aWw7uro5C1ym",
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"outputId": "b33fbf63-171c-4b5b-f33a-b102282b42d2"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Query 1: consultant specialty\n",
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"extract response: {'consultant_specialty': ['Therapist']}\n",
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"Query 2: Consultant name\n",
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"extract response: {'Consultant_name': ['Peter']}\n",
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"Query 3: Consultant location\n",
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"extract response: {'Consultant_location': ['NYC']}\n",
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"Query 4: Consultant Advice\n",
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"extract response: {'Consultant_Advice': ['Be more outgoing.']}\n",
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"output dictionary: \n",
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"{'consultant_specialty': ['Therapist'], 'Consultant_name': ['Peter'], 'Consultant_location': ['NYC'], 'Consultant_Advice': ['Be more outgoing.']}\n"
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]
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}
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],
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"source": [
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"# load the model\n",
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"model = ModelCatalog().load_model(\"slim-extract-tool\",sample=False, temperature=0.0, max_output=200)\n",
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"# loop through the text and queries, calling the model each time\n",
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"output_dict = {}\n",
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"for i, sample in enumerate(Text_to_analyze):\n",
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" for j, query in enumerate(queries_list):\n",
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" print(f\"Query {j+1}: {query}\")\n",
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" response = model.function_call(sample, function=\"extract\", params=[query])\n",
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" output_dict.update(response[\"llm_response\"])\n",
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" if response[\"llm_response\"] == []:\n",
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" print(\"No response\")\n",
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" print(\"extract response: \", response[\"llm_response\"])\n",
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"\n",
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"\n",
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" # display the response on the screen\n",
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"print(\"output dictionary: \" )\n",
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"print(output_dict)"
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]
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}
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],
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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"gpuType": "T4",
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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