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"@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } } }, "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Ov0RXE2Zs2at", "outputId": "51eaf6d5-b1db-4f20-a9c9-07adb560da46" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Mounted at /content/drive\n" ] } ], "source": [ "from google.colab import drive\n", "drive.mount('/content/drive')" ] }, { "cell_type": "code", "source": [ "!pip install gradio\n", "!pip install transformers" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "pQAe4Y4Rs_20", "outputId": "b5ff1523-a3e8-4ab7-b6cc-f60501270564" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: 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AutoTokenizer.from_pretrained(base_model)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 236, "referenced_widgets": [ "e313b0cc4b39472fba5f6b520ab3a6e7", "1ef5aac40bbf4f7bbecbac38caecb2d5", "aa6b247226bb42e7915dc2758b2d232d", "7ffe5bb98aa042e2904774e25369b624", "f4757a5ec55f42b9a0d66bd46cbbb36e", "024ecf01ba314b54a306a60e94a1bdd5", "1baf9e333dc547ecb53f3ef26ce812b9", "6866b01d6ba34c4b837466a30e93c07b", "b18cdd1e22654e3098856208349b5f1e", "45efed67099e45c4a0364e701f1e32eb", "e7fc29787ef84344856a09120389f32d", "4edbc95f10a24b189a0e79241ff85b32", "6f2c58bad2dd46c6b8467f5104b610a3", "7e6f63c2efe04a63999a03d6131ce56a", "77ae90d7e92b48a9b36ff7db470b836a", "e493f8f5498a4a939a0c66a85eaf191f", "c5898fa156ff49cb8c33e74ef61fd25a", "f5bf429ff4c844b7aee2a9e8288cb3f8", "fb591b16c0e044dbb6b2647b805dbf23", "f4d427594da34c3baf5a33570d4f870b", "a77fcb33e2fe402eb6ea3049f371ef13", "c485b291ec58479786edd351044103ce", "1b7f96a9d350409d8f4e0118247748e9", "caa73b1c8e73487ab469deb806e70d40", "d8da27dfaab146a8ab0d3646c216b9be", "7ea09bd1fca44671a919699e9d1291ab", "1352a435d41f4a9d8127fb68baff101e", "d62883a081614ddabfc08ae629d27d45", "7b3b3cffe30e47689ce071bf79150dbf", "447edb84e4b245de90a3ed929f507eb4", "97fb44af3c3e48c3a3d829573c56055a", "a4a2776a7a73457abc39a4ed4550da3e", "bbbf1bcdd5c74eba80d6457692606476", "cfa5759e27a64c6c8337939e7834e17b", "3dffb0ec291a4dfdb1d11b5cef1f5ed6", "20169058ddfb4231821b16e43e9e032c", "0fbfa41014a249588abbf0f4f99c8023", "2f521b4021874155ad19595d7d3c6b30", "a40fdc3db912487296e2081a053855b6", "a4aeabc9652447459960f440b737e924", "5f23d3b89ed94132b03aec776715cb16", "6bff741fe7d54ea098eeadddc17ffa77", "522e520184c0402d8fc2ce2d1355f7f3", "10926435277a4040bdbea6fe457968dc" ] }, "id": "58TcyuIptN2b", "outputId": "0ed8cb8d-ea2a-4f7b-f5d7-b0a7e6e7d7be" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "All model checkpoint layers were used when initializing TFDistilBertForSequenceClassification.\n", "\n", "All the layers of TFDistilBertForSequenceClassification were initialized from the model checkpoint at drive/MyDrive/FIRE/OOD/train_on_sst2/bert.\n", "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" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading: 0%| | 0.00/28.0 [00:00" ], "application/javascript": [ "(async (port, path, width, height, cache, element) => {\n", " if (!google.colab.kernel.accessAllowed && !cache) {\n", " return;\n", " }\n", " element.appendChild(document.createTextNode(''));\n", " const url = await google.colab.kernel.proxyPort(port, {cache});\n", "\n", " const external_link = document.createElement('div');\n", " external_link.innerHTML = `\n", "
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