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"@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + } + } + } + }, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# BERT\n", + "\n", + "Default version of BERT trained by google." + ], + "metadata": { + "id": "LhO2_dJ8RyaM" + } + }, + { + "cell_type": "markdown", + "source": [ + "## huggingface with pytorch backend" + ], + "metadata": { + "id": "2wPOj7OZSVrK" + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0mFq_tFlVGai" + }, + "outputs": [], + "source": [ + "import torch\n", + "from transformers import AutoModel, AutoTokenizer" + ] + }, + { + "cell_type": "code", + "source": [ + "device = \"cuda\" # the device to load the model onto" + ], + "metadata": { + "id": "iO67xiMaVhlq" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')\n", + "model = AutoModel.from_pretrained(\"bert-base-uncased\")\n", + "model.to(device)\n" + ], + "metadata": { + "id": "chEAWaGCV_2t", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000, + "referenced_widgets": [ + "84e413a8135344b19e43087515497946", + "d88364f9efff42498cab927d26e5cc6a", + "8def5e61d59e4539abcca263fbe18262", + "8e3d89e460e246d7a35973c9b8488d0a", + "7c832fc86e1840248dfe002cbbd3e2dc", + "8d5b2bcf1e414d498ea321592843c369", + "6362e08727784e8aa23c7a55a635456e", + "4b5e34d717ae48f4ba407a95d28a5741", + "3b41bbe293c5499c8eb3a47ab3cf94de", + "f746f753af95434c9d1112ea5258faa7", + "e0fef7c1700947df8c310b5715d86d7d", + "9520f283ea9c429589a548438621cda5", + "953cb4b13a9e4907962f398c8cfc46e0", + "2e261879b5e74eb08308711f30ae52e8", + "719f854af93442cbbe0696b13d273712", + "301c82d5db974316bd38b11e2459e5d1", + "c940c5ff100b410d863be608cb1c334d", + "9b6a1981fb2949ebb25f1aced08487cb", + "48db3f58a45e4fafb41312a42d86a607", + "f5c22a090e4e4bc98e2516a752daff0a", + 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optional to access public models or datasets.\n", + " warnings.warn(\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "tokenizer_config.json: 0%| | 0.00/48.0 [00:00=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.25.2)\n", + "Requirement already satisfied: pyarrow>=12.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (14.0.2)\n", + "Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets) (0.6)\n", + "Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.3.8)\n", + "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (2.0.3)\n", + "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.31.0)\n", + "Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.2)\n", + 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/usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.7)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2.0.7)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2024.2.2)\n", + "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n", + "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2023.4)\n", + "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2024.1)\n", + "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.16.0)\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## With PyTorch backend" + ], + "metadata": { + "id": "dD2jiFTffNlB" + } + }, + { + "cell_type": "code", + "source": [ + "from transformers import AutoImageProcessor, ViTForImageClassification\n", + "import torch\n", + "from datasets import load_dataset\n", + "\n", + "dataset = load_dataset(\"huggingface/cats-image\")\n", + "image = dataset[\"test\"][\"image\"][0]\n", + "\n", + "image_processor = AutoImageProcessor.from_pretrained(\"google/vit-base-patch16-224\")\n", + "model = ViTForImageClassification.from_pretrained(\"google/vit-base-patch16-224\")\n", + "\n", + "inputs = image_processor(image, return_tensors=\"pt\")\n", + "\n", + "with torch.no_grad():\n", + " logits = model(**inputs).logits\n", + "\n", + "# model predicts one of the 1000 ImageNet classes\n", + "predicted_label = logits.argmax(-1).item()\n", + "print(model.config.id2label[predicted_label])" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 420, + "referenced_widgets": [ + 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(https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", + "You will be able to reuse this 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", + "/usr/local/lib/python3.10/dist-packages/datasets/load.py:1486: FutureWarning: The repository for huggingface/cats-image contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/huggingface/cats-image\n", + "You can avoid this message in future by passing the argument `trust_remote_code=True`.\n", + "Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.\n", + " warnings.warn(\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Downloading builder script: 0%| | 0.00/2.56k [00:00