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Behind_the_pipeline_Tensorflow

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  1. Behind_the_pipeline_(TensorFlow).ipynb +1871 -0
Behind_the_pipeline_(TensorFlow).ipynb ADDED
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1
+ {
2
+ "cells": [
3
+ {
4
+ "cell_type": "markdown",
5
+ "metadata": {
6
+ "id": "2T7NJZfdhoWW"
7
+ },
8
+ "source": [
9
+ "# Behind the pipeline (TensorFlow)"
10
+ ]
11
+ },
12
+ {
13
+ "cell_type": "markdown",
14
+ "metadata": {
15
+ "id": "JOopAyZ7hoXH"
16
+ },
17
+ "source": [
18
+ "Install the Transformers, Datasets, and Evaluate libraries to run this notebook."
19
+ ]
20
+ },
21
+ {
22
+ "cell_type": "code",
23
+ "execution_count": 1,
24
+ "metadata": {
25
+ "id": "3rss__JGhoXc",
26
+ "outputId": "d5d97fb3-482b-4db5-afb0-e10da55c7e36",
27
+ "colab": {
28
+ "base_uri": "https://localhost:8080/"
29
+ }
30
+ },
31
+ "outputs": [
32
+ {
33
+ "output_type": "stream",
34
+ "name": "stdout",
35
+ "text": [
36
+ "Collecting datasets\n",
37
+ " Downloading datasets-2.14.4-py3-none-any.whl (519 kB)\n",
38
+ "\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/519.3 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[91m━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.2/519.3 kB\u001b[0m \u001b[31m2.6 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━\u001b[0m \u001b[32m430.1/519.3 kB\u001b[0m \u001b[31m6.2 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m519.3/519.3 kB\u001b[0m \u001b[31m5.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
39
+ "\u001b[?25hCollecting evaluate\n",
40
+ " Downloading evaluate-0.4.0-py3-none-any.whl (81 kB)\n",
41
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m81.4/81.4 kB\u001b[0m \u001b[31m8.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
42
+ "\u001b[?25hCollecting transformers[sentencepiece]\n",
43
+ " Downloading transformers-4.32.1-py3-none-any.whl (7.5 MB)\n",
44
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.5/7.5 MB\u001b[0m \u001b[31m20.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
45
+ "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.23.5)\n",
46
+ "Requirement already satisfied: pyarrow>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (9.0.0)\n",
47
+ "Collecting dill<0.3.8,>=0.3.0 (from datasets)\n",
48
+ " Downloading dill-0.3.7-py3-none-any.whl (115 kB)\n",
49
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.3/115.3 kB\u001b[0m \u001b[31m13.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
50
+ "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (1.5.3)\n",
51
+ "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.31.0)\n",
52
+ "Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.1)\n",
53
+ "Collecting xxhash (from datasets)\n",
54
+ " Downloading xxhash-3.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
55
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m18.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
56
+ "\u001b[?25hCollecting multiprocess (from datasets)\n",
57
+ " Downloading multiprocess-0.70.15-py310-none-any.whl (134 kB)\n",
58
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m13.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
59
+ "\u001b[?25hRequirement already satisfied: fsspec[http]>=2021.11.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n",
60
+ "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.8.5)\n",
61
+ "Collecting huggingface-hub<1.0.0,>=0.14.0 (from datasets)\n",
62
+ " Downloading huggingface_hub-0.16.4-py3-none-any.whl (268 kB)\n",
63
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m268.8/268.8 kB\u001b[0m \u001b[31m22.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
64
+ "\u001b[?25hRequirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (23.1)\n",
65
+ "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.1)\n",
66
+ "Collecting responses<0.19 (from evaluate)\n",
67
+ " Downloading responses-0.18.0-py3-none-any.whl (38 kB)\n",
68
+ "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers[sentencepiece]) (3.12.2)\n",
69
+ "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers[sentencepiece]) (2023.6.3)\n",
70
+ "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers[sentencepiece])\n",
71
+ " Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
72
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m40.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
73
+ "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers[sentencepiece])\n",
74
+ " Downloading safetensors-0.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
75
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m39.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
76
+ "\u001b[?25hCollecting sentencepiece!=0.1.92,>=0.1.91 (from transformers[sentencepiece])\n",
77
+ " Downloading sentencepiece-0.1.99-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
78
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m52.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
79
+ "\u001b[?25hRequirement already satisfied: protobuf in /usr/local/lib/python3.10/dist-packages (from transformers[sentencepiece]) (3.20.3)\n",
80
+ "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (23.1.0)\n",
81
+ "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (3.2.0)\n",
82
+ "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.0.4)\n",
83
+ "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.3)\n",
84
+ "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.9.2)\n",
85
+ "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.4.0)\n",
86
+ "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n",
87
+ "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0.0,>=0.14.0->datasets) (4.7.1)\n",
88
+ "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.4)\n",
89
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2.0.4)\n",
90
+ "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2023.7.22)\n",
91
+ "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n",
92
+ "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2023.3)\n",
93
+ "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->datasets) (1.16.0)\n",
94
+ "Installing collected packages: tokenizers, sentencepiece, safetensors, xxhash, dill, responses, multiprocess, huggingface-hub, transformers, datasets, evaluate\n",
95
+ "Successfully installed datasets-2.14.4 dill-0.3.7 evaluate-0.4.0 huggingface-hub-0.16.4 multiprocess-0.70.15 responses-0.18.0 safetensors-0.3.3 sentencepiece-0.1.99 tokenizers-0.13.3 transformers-4.32.1 xxhash-3.3.0\n"
96
+ ]
97
+ }
98
+ ],
99
+ "source": [
100
+ "!pip install datasets evaluate transformers[sentencepiece]"
101
+ ]
102
+ },
103
+ {
104
+ "cell_type": "code",
105
+ "execution_count": 2,
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+ "metadata": {
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+ "id": "YqRRfwGHhoXf",
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+ "outputId": "feec460a-3074-45e4-f481-600ca1a098a2",
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+ "colab": {
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+ "7533d49ee65b4eb7b5206147f382550f",
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+ "88f1ccbbf0764ca586cd557f903ac058",
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+ "66b0134d23074d9ea7569ad20c784b28",
149
+ "99b0e9157fab458198487cce8691fe81",
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+ "ef8c8c3fbef94735a607722a942e04f8",
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+ "76d11ab5050f48deba16d6b9aa0d0568",
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+ "ec960adde27b4e438a09803642fc71a8",
153
+ "4a18ceac740040b6a221c39481a09636",
154
+ "db80ce3109354c55a8356840e0f071e7",
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+ "5142db656cab4b7d9ad246a2b363f708",
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+ "13623bd3096d45af83ef339474b4357f"
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+ ]
158
+ }
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+ },
160
+ "outputs": [
161
+ {
162
+ "output_type": "stream",
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+ "name": "stderr",
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+ "text": [
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+ "No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english and revision af0f99b (https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english).\n",
166
+ "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
167
+ ]
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+ },
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+ {
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+ "output_type": "display_data",
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+ "data": {
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+ "text/plain": [
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+ "Downloading (…)lve/main/config.json: 0%| | 0.00/629 [00:00<?, ?B/s]"
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+ ],
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+ "application/vnd.jupyter.widget-view+json": {
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+ "version_major": 2,
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+ "version_minor": 0,
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+ "model_id": "b05ce34a731f475b82f1058bdc99cfcc"
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+ }
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+ },
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+ "metadata": {}
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+ },
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+ {
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+ "output_type": "display_data",
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+ "data": {
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+ "text/plain": [
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+ "Downloading model.safetensors: 0%| | 0.00/268M [00:00<?, ?B/s]"
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+ ],
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+ "application/vnd.jupyter.widget-view+json": {
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+ "version_major": 2,
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+ "version_minor": 0,
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+ "model_id": "4bbcbf0d4fb24f5e99ca8a03717c3d5f"
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+ }
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+ },
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+ "metadata": {}
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+ },
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+ {
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+ "output_type": "display_data",
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+ "data": {
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+ "text/plain": [
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+ "Downloading (…)okenizer_config.json: 0%| | 0.00/48.0 [00:00<?, ?B/s]"
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+ ],
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+ "application/vnd.jupyter.widget-view+json": {
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+ "version_major": 2,
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+ "version_minor": 0,
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+ "model_id": "02153f3a73bf43ee87914b771c992d9e"
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+ }
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+ },
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+ "metadata": {}
210
+ },
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+ {
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+ "output_type": "display_data",
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+ "data": {
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+ "text/plain": [
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+ "Downloading (…)solve/main/vocab.txt: 0%| | 0.00/232k [00:00<?, ?B/s]"
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+ ],
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+ "application/vnd.jupyter.widget-view+json": {
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+ "version_major": 2,
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+ "version_minor": 0,
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+ "model_id": "7533d49ee65b4eb7b5206147f382550f"
221
+ }
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+ },
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+ "metadata": {}
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+ },
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+ {
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+ "output_type": "execute_result",
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+ "data": {
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+ "text/plain": [
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+ "[{'label': 'POSITIVE', 'score': 0.9598048329353333},\n",
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+ " {'label': 'NEGATIVE', 'score': 0.9994558691978455}]"
231
+ ]
232
+ },
233
+ "metadata": {},
234
+ "execution_count": 2
235
+ }
236
+ ],
237
+ "source": [
238
+ "from transformers import pipeline\n",
239
+ "\n",
240
+ "classifier = pipeline(\"sentiment-analysis\")\n",
241
+ "classifier(\n",
242
+ " [\n",
243
+ " \"I've been waiting for a HuggingFace course my whole life.\",\n",
244
+ " \"I hate this so much!\",\n",
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+ " ]\n",
246
+ ")"
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+ ]
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+ },
249
+ {
250
+ "cell_type": "code",
251
+ "execution_count": 3,
252
+ "metadata": {
253
+ "id": "2rlR988LhoXi"
254
+ },
255
+ "outputs": [],
256
+ "source": [
257
+ "from transformers import AutoTokenizer\n",
258
+ "\n",
259
+ "checkpoint = \"distilbert-base-uncased-finetuned-sst-2-english\"\n",
260
+ "tokenizer = AutoTokenizer.from_pretrained(checkpoint)"
261
+ ]
262
+ },
263
+ {
264
+ "cell_type": "code",
265
+ "execution_count": 4,
266
+ "metadata": {
267
+ "id": "d-lYVpEIhoXn",
268
+ "outputId": "7729b785-e6b1-4553-d864-1c7781fd892a",
269
+ "colab": {
270
+ "base_uri": "https://localhost:8080/"
271
+ }
272
+ },
273
+ "outputs": [
274
+ {
275
+ "output_type": "stream",
276
+ "name": "stdout",
277
+ "text": [
278
+ "{'input_ids': <tf.Tensor: shape=(2, 16), dtype=int32, numpy=\n",
279
+ "array([[ 101, 1045, 1005, 2310, 2042, 3403, 2005, 1037, 17662,\n",
280
+ " 12172, 2607, 2026, 2878, 2166, 1012, 102],\n",
281
+ " [ 101, 1045, 5223, 2023, 2061, 2172, 999, 102, 0,\n",
282
+ " 0, 0, 0, 0, 0, 0, 0]], dtype=int32)>, 'attention_mask': <tf.Tensor: shape=(2, 16), dtype=int32, numpy=\n",
283
+ "array([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],\n",
284
+ " [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=int32)>}\n"
285
+ ]
286
+ }
287
+ ],
288
+ "source": [
289
+ "raw_inputs = [\n",
290
+ " \"I've been waiting for a HuggingFace course my whole life.\",\n",
291
+ " \"I hate this so much!\",\n",
292
+ "]\n",
293
+ "inputs = tokenizer(raw_inputs, padding=True, truncation=True, return_tensors=\"tf\")\n",
294
+ "print(inputs)"
295
+ ]
296
+ },
297
+ {
298
+ "cell_type": "code",
299
+ "execution_count": 5,
300
+ "metadata": {
301
+ "id": "QRk2owv8hoXp",
302
+ "outputId": "7a4d297e-fac3-4f96-fdf3-539e64c105e1",
303
+ "colab": {
304
+ "base_uri": "https://localhost:8080/"
305
+ }
306
+ },
307
+ "outputs": [
308
+ {
309
+ "output_type": "stream",
310
+ "name": "stderr",
311
+ "text": [
312
+ "Some weights of the PyTorch model were not used when initializing the TF 2.0 model TFDistilBertModel: ['classifier.weight', 'pre_classifier.weight', 'classifier.bias', 'pre_classifier.bias']\n",
313
+ "- This IS expected if you are initializing TFDistilBertModel from a PyTorch model trained on another task or with another architecture (e.g. initializing a TFBertForSequenceClassification model from a BertForPreTraining model).\n",
314
+ "- This IS NOT expected if you are initializing TFDistilBertModel from a PyTorch model that you expect to be exactly identical (e.g. initializing a TFBertForSequenceClassification model from a BertForSequenceClassification model).\n",
315
+ "All the weights of TFDistilBertModel were initialized from the PyTorch model.\n",
316
+ "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFDistilBertModel for predictions without further training.\n"
317
+ ]
318
+ }
319
+ ],
320
+ "source": [
321
+ "from transformers import TFAutoModel\n",
322
+ "\n",
323
+ "checkpoint = \"distilbert-base-uncased-finetuned-sst-2-english\"\n",
324
+ "model = TFAutoModel.from_pretrained(checkpoint)"
325
+ ]
326
+ },
327
+ {
328
+ "cell_type": "code",
329
+ "execution_count": 6,
330
+ "metadata": {
331
+ "id": "i56DUrQZhoXq",
332
+ "outputId": "c988ad63-2b9e-406a-f328-01f006a9edbb",
333
+ "colab": {
334
+ "base_uri": "https://localhost:8080/"
335
+ }
336
+ },
337
+ "outputs": [
338
+ {
339
+ "output_type": "stream",
340
+ "name": "stdout",
341
+ "text": [
342
+ "(2, 16, 768)\n"
343
+ ]
344
+ }
345
+ ],
346
+ "source": [
347
+ "outputs = model(inputs)\n",
348
+ "print(outputs.last_hidden_state.shape)"
349
+ ]
350
+ },
351
+ {
352
+ "cell_type": "code",
353
+ "execution_count": 7,
354
+ "metadata": {
355
+ "id": "Bd8y41EehoXt",
356
+ "outputId": "fdac52f9-d928-4d00-f800-e1da73238094",
357
+ "colab": {
358
+ "base_uri": "https://localhost:8080/"
359
+ }
360
+ },
361
+ "outputs": [
362
+ {
363
+ "output_type": "stream",
364
+ "name": "stderr",
365
+ "text": [
366
+ "All PyTorch model weights were used when initializing TFDistilBertForSequenceClassification.\n",
367
+ "\n",
368
+ "All the weights of TFDistilBertForSequenceClassification were initialized from the PyTorch model.\n",
369
+ "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFDistilBertForSequenceClassification for predictions without further training.\n"
370
+ ]
371
+ }
372
+ ],
373
+ "source": [
374
+ "from transformers import TFAutoModelForSequenceClassification\n",
375
+ "\n",
376
+ "checkpoint = \"distilbert-base-uncased-finetuned-sst-2-english\"\n",
377
+ "model = TFAutoModelForSequenceClassification.from_pretrained(checkpoint)\n",
378
+ "outputs = model(inputs)"
379
+ ]
380
+ },
381
+ {
382
+ "cell_type": "code",
383
+ "execution_count": 8,
384
+ "metadata": {
385
+ "id": "HOrL6t_9hoXw",
386
+ "outputId": "0c5ad55c-466d-4f0f-afef-27745d7ff7da",
387
+ "colab": {
388
+ "base_uri": "https://localhost:8080/"
389
+ }
390
+ },
391
+ "outputs": [
392
+ {
393
+ "output_type": "stream",
394
+ "name": "stdout",
395
+ "text": [
396
+ "(2, 2)\n"
397
+ ]
398
+ }
399
+ ],
400
+ "source": [
401
+ "print(outputs.logits.shape)"
402
+ ]
403
+ },
404
+ {
405
+ "cell_type": "code",
406
+ "execution_count": 9,
407
+ "metadata": {
408
+ "id": "IDzFalBVhoXx",
409
+ "outputId": "dce5305b-60b2-484c-f7af-b1a65cea476d",
410
+ "colab": {
411
+ "base_uri": "https://localhost:8080/"
412
+ }
413
+ },
414
+ "outputs": [
415
+ {
416
+ "output_type": "stream",
417
+ "name": "stdout",
418
+ "text": [
419
+ "tf.Tensor(\n",
420
+ "[[-1.5606955 1.6122805]\n",
421
+ " [ 4.169232 -3.3464477]], shape=(2, 2), dtype=float32)\n"
422
+ ]
423
+ }
424
+ ],
425
+ "source": [
426
+ "print(outputs.logits)"
427
+ ]
428
+ },
429
+ {
430
+ "cell_type": "code",
431
+ "execution_count": 10,
432
+ "metadata": {
433
+ "id": "9q5VZ8BdhoXz",
434
+ "outputId": "154f40fc-89cf-493c-cf93-34c11c43c6be",
435
+ "colab": {
436
+ "base_uri": "https://localhost:8080/"
437
+ }
438
+ },
439
+ "outputs": [
440
+ {
441
+ "output_type": "stream",
442
+ "name": "stdout",
443
+ "text": [
444
+ "tf.Tensor(\n",
445
+ "[[4.0195443e-02 9.5980453e-01]\n",
446
+ " [9.9945587e-01 5.4418371e-04]], shape=(2, 2), dtype=float32)\n"
447
+ ]
448
+ }
449
+ ],
450
+ "source": [
451
+ "import tensorflow as tf\n",
452
+ "\n",
453
+ "predictions = tf.math.softmax(outputs.logits, axis=-1)\n",
454
+ "print(predictions)"
455
+ ]
456
+ },
457
+ {
458
+ "cell_type": "code",
459
+ "execution_count": 11,
460
+ "metadata": {
461
+ "id": "5UngefnwhoX0",
462
+ "outputId": "44114e0b-d4ac-4bc1-a0a3-8ff13dc27e75",
463
+ "colab": {
464
+ "base_uri": "https://localhost:8080/"
465
+ }
466
+ },
467
+ "outputs": [
468
+ {
469
+ "output_type": "execute_result",
470
+ "data": {
471
+ "text/plain": [
472
+ "{0: 'NEGATIVE', 1: 'POSITIVE'}"
473
+ ]
474
+ },
475
+ "metadata": {},
476
+ "execution_count": 11
477
+ }
478
+ ],
479
+ "source": [
480
+ "model.config.id2label"
481
+ ]
482
+ }
483
+ ],
484
+ "metadata": {
485
+ "colab": {
486
+ "name": "Behind the pipeline (TensorFlow)",
487
+ "provenance": []
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+ },
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+ "language_info": {
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+ "name": "python"
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+ },
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+ "kernelspec": {
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