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/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": [ "dedef0fdf6514058936944459069cac8", "766b67493b1540ff914d22d0f03d3da4", "bf2c1485447c49b6970dceafecdf5255", "4dd1432029174225b4ec23cb758aebb7", "3e3953a44dbb4f5abfc6c13062c5288d", "e161fb9931b240b79cdba2ac00b3e497", "6bbac2f041ef441786ababc73890b39a", "ac2d9c54c6b74be3a56d89a01b7c9ac9", "12341b33470a46b3befa2204edde8da6", "fa8b4904e23743a9979a3be43a18d4ea", "0300536ae11a4f42a0e7845fcd7b73b5", "41c8a2aba9d94ba5894fab1c2596ecaa", "a40872e0dd0a4075a60911f196623e8e", "e3d05487e4554979a80ecd8fec6e6b51", "ff4cc39670564728b71775d0aab3461e", "9054dedda8c7476e9dc43f932ee66513", "a93f8873d28148e8b11b5b8d7fbd267a", "af4159affa214d5996444ef6195f18af", "61c5679d6fea4569a148b5c0abab8729", "c864a752150d443d8448d5d3a55f51ff", "1c2447ac31c84995b094d4600779b021", "5692b3d0efe44c2bb3a26abcac0eae7e", "a04b1ca672f3439ba778be819e14d0ee", "8eb0f92749e04825a5ba7bfd66aab37e", "9490bac8167c4e268887c0fe62ee9b3c", "fa7696fcf5b64efa8ad60a7806f09020", "43ef6f882a8841a8be70c837e719aa2b", "b0a5870df9a64f74864de8009bf72481", "c2f6b8a4077e45b9b7f6ef5e1784a9e1", "97d7b0b001ff4bda9373022771d892ec", "656832770baf434e9246f237181e7e34", "475d5bd5b4844803bf94bc06f0c6cc7b", "942dc5ec070c4287a99b83bad051caa4", "a19f222774154c8587e729013f800a15", "9995f5d0eeed48389898efb8a5f6436e", "facc9dd3d17445238f4a5606b5564540", "fb3deabf38a04f158c62f90a5082c6d2", "ab623948ba574669a7d2bf150b79249f", "f931e97c29e04312ba4d37c3b220166d", "ba952e8d7eaa41b1829f339156fd09b9", "222c06694cd644f3aea09bdcadf3badb", "56df248a4e7f4a639dcc91f27a6f26df", "c2a0310238384d7fb859d53213150918", "cbaa95b5780b471fa809c3b78d89199b", "39634062a4d54e3f9c5132122361ddbe", "ab89169d885d487ab05c2332d877c911", "37ce627b303f48f8a30bc41ac43c5b73", "bcd9427c16314715aa0310e48c689f9c", "1735cad9dd394093a749d424fcb55652", "a2c730a180e849df89c9fd3b9f33aa77", "837c565632ad4e5b8f13ae5d46633410", "80c00436aaab4e57a25ef5cd6bfbf4e5", "0bc1480df432458a898432fc13aef292", "1cae8726c2784af098bced7526b3aa8d", "00e8781fe1044921a488b3ccf4149f20", "b55a75efd4a04f78a621b52332911670", "73e3b9ba14da4d2ab15273f4ab57b04c", "0eca67fd2b0e4e93ab7f8c0421b6bdb2", "a28f72f99b624709ba3a961678fb3a58", "3c82e81097b94e43a32c28be64dc7251", "a7eba91445034bc9b191f1f9ab10af0e", "eeb7cbaa02b943c3a3a5d86b0211d61f", "ad303321f323477a8d890f64f8d58122", "b09992865d994f14a09a9a3a3e8cf751", "e1c5dda4c27d4f7b9ccd502254d38839", "f7416cad4c8c4dd788d40635fac1d06b" ] }, "id": "2jw918j8bVrG", "outputId": "85b96cfc-acac-4629-f364-93b9d03cd2fc" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n", "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", "To authenticate with the Hugging Face Hub, create a token in your settings tab (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