diff --git a/huggingface-transformers/README.md b/huggingface-transformers/README.md index bb524af88b..9e230859da 100644 --- a/huggingface-transformers/README.md +++ b/huggingface-transformers/README.md @@ -1,24 +1,42 @@ # Hugging Face Transformers: Leverage Open-Source AI in Python -This folder contains the materials for the tutorial (Hugging Face Transformers: Leverage Open-Source AI in Python)[https://realpython.com/huggingface-transformers/]. +This folder contains the materials for the tutorial [Hugging Face Transformers: Leverage Open-Source AI in Python](https://realpython.com/huggingface-transformers/). -Transformers is available on [PyPI](https://pypi.org/) and you can install it with [pip](https://realpython.com/what-is-pip/). Open a terminal or command prompt, create a new virtual environment, and then run the following command: +## Installation -```console -(venv) $ python -m pip install transformers +Create and activate a virtual environment, and then install the required dependencies: + +```sh +(venv) $ python -m pip install transformers torch pillow notebook ipywidgets +``` + +Alternatively, if you use [Poetry](https://realpython.com/dependency-management-python-poetry/), then you can issue the following command to handle the installation process for you: + +```sh +$ poetry install ``` -This command will install the latest version of Transformers from PyPI onto your machine. Throughout this tutorial, you'll also leverage [PyTorch](https://realpython.com/pytorch-vs-tensorflow/) to interact with models at a lower level. You can install PyTorch with the following command: +## Usage -```console -(venv) $ python -m pip install torch +Run the sample Python scripts: + +```sh +(venv) $ python auto_classes.py +(venv) $ python running_pipelines.py ``` -To verify that the installations were successful, start a [Python REPL](https://realpython.com/python-repl/) and import `transformers` and `torch`: +Run the sample Jupyter notebook: -```pycon ->>> import transformers ->>> import torch +```sh +(venv) $ python -m jupyter notebook gpus_google_colab.ipynb ``` -If the imports run without errors, then you've successfully installed the dependencies needed for this tutorial. +Note that if you run this notebook in Google Colab, then you'll need to update the path to the `requirements.txt` file and the `DATA_PATH` constant accordingly: + +```diff +-!pip install -r requirements.txt ++!pip install -r /content/requirements.txt + +-DATA_PATH = "Scraped_Car_Review_dodge.csv" ++DATA_PATH = "/content/Scraped_Car_Review_dodge.csv" +``` diff --git a/huggingface-transformers/cars_data/Scraped_Car_Review_dodge.csv b/huggingface-transformers/Scraped_Car_Review_dodge.csv similarity index 100% rename from huggingface-transformers/cars_data/Scraped_Car_Review_dodge.csv rename to huggingface-transformers/Scraped_Car_Review_dodge.csv diff --git a/huggingface-transformers/gpus_google_colab.ipynb b/huggingface-transformers/gpus_google_colab.ipynb index 6244659be1..19ffacc6a3 100644 --- a/huggingface-transformers/gpus_google_colab.ipynb +++ b/huggingface-transformers/gpus_google_colab.ipynb @@ -1,117 +1,278 @@ { - "nbformat": 4, - "nbformat_minor": 0, + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "TCdF0YVM5JSp", + "outputId": "cf216217-3aca-4673-d34d-76a009fb3fee" + }, + "outputs": [], + "source": [ + "!pip install -r requirements.txt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SpXQWhLFCWvP" + }, + "outputs": [], + "source": [ + "DATA_PATH = \"Scraped_Car_Review_dodge.csv\"\n", + "\n", + "import time\n", + "from tqdm import tqdm\n", + "import polars as pl\n", + "import torch\n", + "from transformers import (\n", + " pipeline,\n", + " TextClassificationPipeline,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "t9ajxcjvDMBb", + "outputId": "32cc9374-ad6a-4ae8-b603-3e8cc40ddeea" + }, + "outputs": [], + "source": [ + "reviews_list = pl.read_csv(DATA_PATH)[\"Review\"].to_list()\n", + "len(reviews_list)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 71 + }, + "id": "xu7-TqjvDQAs", + "outputId": "8acbc426-cf4c-47a3-c81d-925077486690" + }, + "outputs": [], + "source": [ + "reviews_list[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "t8CKs4XA3_Vt" + }, + "outputs": [], + "source": [ + "def time_text_classifier(\n", + " text_pipeline: TextClassificationPipeline,\n", + " texts: list[str],\n", + " batch_size: int = 1,\n", + ") -> None:\n", + " \"\"\"Time how long it takes a TextClassificationPipeline\n", + " to run inference on a list of texts\"\"\"\n", + "\n", + " texts_generator = (t for t in texts)\n", + " pipeline_iterable = tqdm(\n", + " text_pipeline(\n", + " texts_generator,\n", + " batch_size=batch_size,\n", + " truncation=True,\n", + " max_length=500,\n", + " ),\n", + " total=len(texts),\n", + " )\n", + "\n", + " for result in pipeline_iterable:\n", + " pass" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 411, + "referenced_widgets": [ + "45612e3607b6492e8b30a8f2bb8a960c", + "33334dfb46ff4b0aacac3edc5ee88620", + 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2))\n", - " Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n", - "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n", - "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n", - "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n", - "Collecting nvidia-curand-cu12==10.3.2.106 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n", - "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n", - "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n", - "Collecting nvidia-nccl-cu12==2.19.3 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Downloading nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl (166.0 MB)\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m166.0/166.0 MB\u001b[0m \u001b[31m3.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[?25hCollecting nvidia-nvtx-cu12==12.1.105 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n", - "Collecting triton==2.2.0 (from torch==2.2.0->-r /content/requirements.txt (line 2))\n", - " Downloading 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(2.1.5)\n", - "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.41.1->-r /content/requirements.txt (line 1)) (3.3.2)\n", - "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.41.1->-r /content/requirements.txt (line 1)) (3.7)\n", - "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.41.1->-r /content/requirements.txt (line 1)) (2.0.7)\n", - "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.41.1->-r /content/requirements.txt (line 1)) (2024.6.2)\n", - "Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch==2.2.0->-r /content/requirements.txt (line 2)) (1.3.0)\n", - "Installing collected packages: triton, polars, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, transformers, torch, accelerate\n", - " Attempting uninstall: triton\n", - " Found existing installation: triton 2.3.0\n", - " Uninstalling triton-2.3.0:\n", - " Successfully uninstalled triton-2.3.0\n", - " Attempting uninstall: polars\n", - " Found existing installation: polars 0.20.2\n", - " Uninstalling polars-0.20.2:\n", - " Successfully uninstalled polars-0.20.2\n", - " Attempting uninstall: transformers\n", - " Found existing installation: transformers 4.41.2\n", - " Uninstalling transformers-4.41.2:\n", - " Successfully uninstalled transformers-4.41.2\n", - " Attempting uninstall: torch\n", - " Found existing installation: torch 2.3.0+cu121\n", - " Uninstalling torch-2.3.0+cu121:\n", - " Successfully uninstalled torch-2.3.0+cu121\n", - "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", - "torchaudio 2.3.0+cu121 requires torch==2.3.0, but you have torch 2.2.0 which is incompatible.\n", - "torchtext 0.18.0 requires torch>=2.3.0, but you have torch 2.2.0 which is incompatible.\n", - "torchvision 0.18.0+cu121 requires torch==2.3.0, but you have torch 2.2.0 which is incompatible.\u001b[0m\u001b[31m\n", - "\u001b[0mSuccessfully installed accelerate-0.30.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105 polars-0.20.31 torch-2.2.0 transformers-4.41.1 triton-2.2.0\n" - ] - } - ], - "source": [ - "!pip install -r /content/requirements.txt" - ] - }, - { - "cell_type": "code", - "source": [ - "DATA_PATH = \"/content/Scraped_Car_Review_dodge.csv\"\n", - "\n", - "import time\n", - "from tqdm import tqdm\n", - "import polars as pl\n", - "import torch\n", - "from transformers import (\n", - " pipeline,\n", - " TextClassificationPipeline,\n", - ")" - ], - "metadata": { - "id": "SpXQWhLFCWvP" - }, - "execution_count": 2, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "reviews_list = pl.read_csv(DATA_PATH)[\"Review\"].to_list()\n", - "len(reviews_list)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "t9ajxcjvDMBb", - "outputId": "32cc9374-ad6a-4ae8-b603-3e8cc40ddeea" - }, - "execution_count": 3, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "8499" - ] - }, - "metadata": {}, - "execution_count": 3 - } - ] - }, - { - "cell_type": "code", - "source": [ - "reviews_list[0]" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 71 - }, - "id": "xu7-TqjvDQAs", - "outputId": "8acbc426-cf4c-47a3-c81d-925077486690" - }, - "execution_count": 4, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "\" It's been a great delivery vehicle for my cafe business good power, economy match easily taken care of. Havent repaired anything or replaced anything but tires and normal maintenance items. Upgraded tires to Michelin LX series helped fuel economy. Would buy another in a second\"" - ], - "application/vnd.google.colaboratory.intrinsic+json": { - "type": "string" - } - }, - "metadata": {}, - "execution_count": 4 - } - ] - }, - { - "cell_type": "code", - "source": [ - "def time_text_classifier(\n", - " text_pipeline: TextClassificationPipeline,\n", - " texts: list[str],\n", - " batch_size: int = 1,\n", - ") -> None:\n", - " \"\"\"Time how long it takes a TextClassificationPipeline\n", - " to run inference on a list of texts\"\"\"\n", - "\n", - " texts_generator = (t for t in texts)\n", - " pipeline_iterable = tqdm(\n", - " text_pipeline(\n", - " texts_generator,\n", - " batch_size=batch_size,\n", - " truncation=True,\n", - " max_length=500,\n", - " ),\n", - " total=len(texts),\n", - " )\n", - "\n", - " for result in pipeline_iterable:\n", - " pass" - ], - "metadata": { - "id": "t8CKs4XA3_Vt" - }, - "execution_count": 5, - "outputs": [] - }, - { - "cell_type": "code", - "source": [ - "model_name = \"cardiffnlp/twitter-roberta-base-sentiment-latest\"\n", - "sentiment_pipeline_cpu = pipeline(model=model_name, device=-1)\n", - "sentiment_pipeline_gpu = pipeline(model=model_name, device=0)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 411, - "referenced_widgets": [ - "45612e3607b6492e8b30a8f2bb8a960c", - "33334dfb46ff4b0aacac3edc5ee88620", - "2d49435605144c4b9c0f5a6ff6c590e8", - "42107b0497e046e79ca6ce46d727b48a", - "8fa49dfab1964359903778e502ae308e", - "afc5e3671d834395953894a8b1b49c18", - "5ef4d00a08d44468858bd490a6c29f5e", - "c57c15d106184a1abf1c957a7ba1d035", - "360d8594dee942d4b444a7064f8de7d4", - "7ba363a600b048d8b333885b65c1dc3f", - "d60e253af7d7403bbb67057d5582f583", - "13db8dca8461421eba8adb839ae744a3", - "a34871b3c6524544bf444132d9c27027", - "c8ce069155cf4200aaad6ccb7b53b5a4", - "19c46af8e37a48bd9859a94a979c384b", - "e5c43bb0386c4947a84578b9bebf5dc5", - "077a554bbf5d4b9d9db387b76af8d58c", - "79132761addd489f847e550187e90aaf", - "9e613d7199764ecdaef3122246dd4bfd", - "f6a99624add143cbb6d98354e5239ae8", - "1995505e3b4b4da2a35e9460cd7e3a8d", - "15015394b18747f9b793f44a6b641afc", - "8835293ed341467387cbc9277364474c", - "388cd1f6e14f4070a28b85caa44da801", - "e0c14432a0fd42e5bf853aa4a958d9d4", - "5f74162579a744e3aa5f708df3a005ed", - "9177168ceb2b4c46839d6c96256363de", - "e625d250275d4d479de51e187d58c235", - "5f571f12e81a4c10b093bc20893b2d5b", - "8c845dee08ef4ecab9d8d845b13adc54", - "ea5f048680b44b2aaa789fd3a69e251c", - "ccd5b3e170cc4ac38083b6ea7e6e3abc", - "2af2e029e23a4d68bd70ae1e67bb6bb3", - "f1664fcced514a3992b1d4bbc773835a", - "faa65e87cb3f4b2898fc2ad4a7ac5385", - "2f9db4ff62df4ef1b2d0c6bc556a20f8", - "46daa8d1757a4bbc9b01b32c8c25fb47", - "7a8aab9c89834536bfa7a264f7805786", - "f986e06c1b5d4fb4b955be8a20dab965", - "a97c7b068d1e4612a07c50ea57a31777", - "0a261733ee424bad9b8bf11ceafaa5d0", - "b0c8a57111e2404a916ef4d2f8ba9b5a", - "a7f66de12fe341f9983c520213d5f4c2", - "a0a7b320b5a84b188cbb923edaaf0f7e", - 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secret in all of your notebooks.\n", - "Please note that authentication is recommended but still optional to access public models or datasets.\n", - " warnings.warn(\n" - ] - }, - { - "output_type": "display_data", - "data": { - "text/plain": [ - "config.json: 0%| | 0.00/929 [00:00=3.8.0" files = [ - {file = "accelerate-0.30.1-py3-none-any.whl", hash = "sha256:8dd4edd532a4dac72558c5fe6fe8cb70d0c8ec9e8733f48db97d51ee41cbe763"}, - {file = "accelerate-0.30.1.tar.gz", hash = "sha256:96779c618889646b86dc928c9e55e86e50a7ccab59e1692e22096481977ae682"}, + {file = "accelerate-0.32.1-py3-none-any.whl", hash = "sha256:71fcf4be00872194071de561634268b71417d7f5b16b178e2fa76b6f117c52b0"}, + {file = "accelerate-0.32.1.tar.gz", hash = "sha256:3999acff0237cd0d4f9fd98b42d5a3163544777b53fc4f1eec886b77e992d177"}, ] [package.dependencies] huggingface-hub = "*" -numpy = ">=1.17" +numpy = ">=1.17,<2.0.0" packaging = ">=20.0" psutil = "*" pyyaml = "*" @@ -31,6 +31,26 @@ test-prod = ["parameterized", "pytest 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(>=6.0.0)", "setuptools (>=65)"] +docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"] +optional = ["python-socks", "wsaccel"] +test = ["websockets"] + +[[package]] +name = "widgetsnbextension" +version = "4.0.11" +description = "Jupyter interactive widgets for Jupyter Notebook" +optional = false +python-versions = ">=3.7" +files = [ + {file = "widgetsnbextension-4.0.11-py3-none-any.whl", hash = "sha256:55d4d6949d100e0d08b94948a42efc3ed6dfdc0e9468b2c4b128c9a2ce3a7a36"}, + {file = "widgetsnbextension-4.0.11.tar.gz", hash = "sha256:8b22a8f1910bfd188e596fe7fc05dcbd87e810c8a4ba010bdb3da86637398474"}, +] [metadata] lock-version = "2.0" python-versions = "^3.12" -content-hash = "9b3e080c823182903eedde212c1be24cb81bae9320220a0f64ad1cf49d3f764d" +content-hash = "bd6861bbcb64313584ec9ccf6ad674a821f0e3435350aa9f1566a47e944b7e27" diff --git a/huggingface-transformers/pyproject.toml b/huggingface-transformers/pyproject.toml index 0b0e36be2a..ce8b0c1107 100644 --- a/huggingface-transformers/pyproject.toml +++ b/huggingface-transformers/pyproject.toml @@ -1,5 +1,5 @@ [tool.poetry] -name = "realpython-hugging-face" +name = "huggingface-transformers" version = "0.1.0" description = "" authors = ["hfhoffman1144 "] @@ -7,17 +7,13 @@ readme = "README.md" [tool.poetry.dependencies] python = "^3.12" -transformers = "^4.41.1" -torch = "2.2.0" -ipykernel = "^6.29.4" -accelerate = "^0.30.1" -packaging = "^24.0" -setuptools = "^70.0.0" -wheel = "^0.43.0" -black = "^24.4.2" -flake8 = "^7.0.0" -ruff = "^0.4.8" -polars = "^1.1.0" +accelerate = "^0.32.1" +ipywidgets = "^8.1.3" +notebook = "^7.2.1" +pillow = "^10.4.0" +polars = "^1.2.0" +torch = "^2.3.1" +transformers = "^4.42.4" [build-system] diff --git a/huggingface-transformers/requirements.txt b/huggingface-transformers/requirements.txt index 2e6e1da7a9..c4aa829761 100644 --- a/huggingface-transformers/requirements.txt +++ b/huggingface-transformers/requirements.txt @@ -1,4 +1,4 @@ -transformers==4.41.1 -torch==2.2.0 -accelerate==0.30.1 -polars==1.1.0 \ No newline at end of file +transformers==4.42.4 +torch==2.3.1 +accelerate==0.32.1 +polars==1.2.0