diff --git a/examples/huggingface/README.md b/examples/huggingface/README.md new file mode 100644 index 00000000..c6b56f4c --- /dev/null +++ b/examples/huggingface/README.md @@ -0,0 +1,5 @@ +# Huggingface + +[Huggingface](https://huggingface.co/) is a website that provides tools for AI tasks. Including a free place to host and share AI models. + +The files in this folder are focused on making use of the Huggingface's related tools. diff --git a/examples/huggingface/share_models.ipynb b/examples/huggingface/share_models.ipynb new file mode 100644 index 00000000..5638a5ed --- /dev/null +++ b/examples/huggingface/share_models.ipynb @@ -0,0 +1,1830 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "view-in-github" + }, + "source": [ + "\"Open\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "4syF6X3Fl5dg", + "outputId": "d4c21587-73a1-4e3f-d4c5-9a22e2fbd3f0" + }, + "outputs": [], + "source": [ + "%pip install -q git+https://github.com/mit-han-lab/torchquantum.git" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8J3xd8iWSEX0" + }, + "source": [ + "# login with your writing token\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 331, + "referenced_widgets": [ + "03ed14345fcd430fa4d692440b2b92de", + "5d56e244ff4a4a8c870e78dfe6ce0f4e", + "74550344bf054abd969ab40f5a90850e", + "c22dddecf8bd4b258e39dcd17559a07c", + "4f1ced08708b4070af3a09ab1bfd5c4a", + "425bd24e216b4b1392670b138d33e795", + "7ac966c2fff74b999086816a16ac9825", + "35a3481cf34d4b72ad1266a9664e2db4", + "3862dbd096054b7dbd3b9a3d26941a00", + "48e27c9c79854a2bbad92ca05cbf6842", + "340be088856c42f082c95c6a3db3f4b1", + "d5fd0caaeb154cf28e8ea9d72587fe0d", + "f9e45fc510a1459c8cb07b1ecc3b8514", + "586cbbcb2b3448b4a8bcf904965b25db", + "b0f383d785134544b2fd7e2bf3e54b33", + "72e8d4713c574538aeebcee32af4960d", + "57537ab729da49e3a53fe8e42fbe772c" + ] + }, + "id": "ydSz4YpbUVU_", + "outputId": "958b42a4-3084-462e-e814-75324adfed09" + }, + "outputs": [], + "source": [ + "# token can be found here https://huggingface.co/settings/tokens\n", + "from huggingface_hub import notebook_login\n", + "\n", + "notebook_login()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hH800Lx4XFuz" + }, + "source": [ + "# Create an AI model\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "6s9D_oxmRaYY" + }, + "outputs": [], + "source": [ + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "import torchquantum as tq\n", + "import torchquantum.functional as tqf\n", + "from huggingface_hub import PyTorchModelHubMixin\n", + "\n", + "\n", + "class QFCModel(nn.Module, PyTorchModelHubMixin, tags=[\"torchquantum\"]):\n", + " def __init__(self, n_wires):\n", + " super().__init__()\n", + "\n", + " self.n_wires = n_wires # an init parameter\n", + "\n", + " self.measure = tq.MeasureAll(tq.PauliZ)\n", + "\n", + " self.encoder_gates = [tqf.rx] * 4 + [tqf.ry] * 4 + [tqf.rz] * 4 + [tqf.rx] * 4\n", + " self.rx0 = tq.RX(has_params=True, trainable=True)\n", + " self.ry0 = tq.RY(has_params=True, trainable=True)\n", + " self.rz0 = tq.RZ(has_params=True, trainable=True)\n", + " self.crx0 = tq.CRX(has_params=True, trainable=True)\n", + "\n", + " def forward(self, x):\n", + " bsz = x.shape[0]\n", + " # down-sample the image\n", + " x = F.avg_pool2d(x, 6).view(bsz, 16)\n", + "\n", + " # create a quantum device to run the gates\n", + " qdev = tq.QuantumDevice(n_wires=self.n_wires, bsz=bsz, device=x.device)\n", + "\n", + " # encode the classical image to quantum domain\n", + " for k, gate in enumerate(self.encoder_gates):\n", + " gate(qdev, wires=k % self.n_wires, params=x[:, k])\n", + "\n", + " # add some trainable gates (need to instantiate ahead of time)\n", + " self.rx0(qdev, wires=0)\n", + " self.ry0(qdev, wires=1)\n", + " self.rz0(qdev, wires=3)\n", + " self.crx0(qdev, wires=[0, 2])\n", + "\n", + " # add some more non-parameterized gates (add on-the-fly)\n", + " qdev.h(wires=3)\n", + " qdev.sx(wires=2)\n", + " qdev.cnot(wires=[3, 0])\n", + " qdev.qubitunitary(\n", + " wires=[1, 2],\n", + " params=[[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1j], [0, 0, -1j, 0]],\n", + " )\n", + "\n", + " # perform measurement to get expectations (back to classical domain)\n", + " x = self.measure(qdev).reshape(bsz, 2, 2)\n", + "\n", + " # classification\n", + " x = x.sum(-1).squeeze()\n", + " x = F.log_softmax(x, dim=1)\n", + "\n", + " return x\n", + "\n", + "\n", + "model = QFCModel(n_wires=4)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "083_CavNXjnf" + }, + "source": [ + "# push your weights to huggingface\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "eAVkBtd1XLqj" + }, + "source": [ + "now you can push your weights to Hugginface or you can use `model.save_pretrained(\"path\")`\n", + "to save your model locally\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 84, + "referenced_widgets": [ + "33d6236ffcb449768358e100ecadff57", + 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class to load the model\n", + "# no need to reinitialize the model or manually load the weights\n", + "# from pretrained can also be used to load a local model\n", + "new_model = QFCModel.from_pretrained(\"not-lain/qfc-model\", force_download=True)" + ] + } + ], + "metadata": { + "colab": { + "include_colab_link": true, + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.11.3" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "03ed14345fcd430fa4d692440b2b92de": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "VBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "VBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "VBoxView", + "box_style": 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