use load by image captioning

vit_gpt2_image_captioning_gradioload.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "V8i3gjxY85ps",
+        "outputId": "b5286759-f627-4e7d-89fb-91ced8842cad"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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+            "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.8/dist-packages (from uvicorn->gradio) (8.1.3)\n",
+            "Collecting h11>=0.8\n",
+            "  Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
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+            "Building wheels for collected packages: ffmpy\n",
+            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for ffmpy: filename=ffmpy-0.3.0-py3-none-any.whl size=4711 sha256=13f8ffda7263e49659b8cfa6e64058f5b17b4ea5d25f283bfe79404460f085ff\n",
+            "  Stored in directory: /root/.cache/pip/wheels/ff/5b/59/913b443e7369dc04b61f607a746b6f7d83fb65e2e19fcc958d\n",
+            "Successfully built ffmpy\n",
+            "Installing collected packages: rfc3986, pydub, ffmpy, websockets, uc-micro-py, sniffio, python-multipart, pycryptodome, orjson, mdurl, h11, aiofiles, uvicorn, markdown-it-py, linkify-it-py, anyio, starlette, mdit-py-plugins, httpcore, httpx, fastapi, gradio\n",
+            "Successfully installed aiofiles-23.1.0 anyio-3.6.2 fastapi-0.93.0 ffmpy-0.3.0 gradio-3.20.1 h11-0.14.0 httpcore-0.16.3 httpx-0.23.3 linkify-it-py-2.0.0 markdown-it-py-2.2.0 mdit-py-plugins-0.3.3 mdurl-0.1.2 orjson-3.8.7 pycryptodome-3.17 pydub-0.25.1 python-multipart-0.0.6 rfc3986-1.5.0 sniffio-1.3.0 starlette-0.25.0 uc-micro-py-1.0.1 uvicorn-0.20.0 websockets-10.4\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install gradio"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import gradio as gr\n",
+        "gr.Interface.load(\n",
+        "    'huggingface/nlpconnect/vit-gpt2-image-captioning',\n",
+        "    inputs = gr.Image(label=\"Carga una imagen\"),\n",
+        "    title = \"Classificator\",\n",
+        "    description = \"Obtener descripcion por imagen\"\n",
+        ").launch()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 634
+        },
+        "id": "TFIAntoh9MCp",
+        "outputId": "53099e44-244d-41c3-aef8-8a3060baf087"
+      },
+      "execution_count": 5,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Fetching model from: https://huggingface.co/nlpconnect/vit-gpt2-image-captioning\n",
+            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
+            "Note: opening Chrome Inspector may crash demo inside Colab notebooks.\n",
+            "\n",
+            "To create a public link, set `share=True` in `launch()`.\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<IPython.core.display.Javascript object>"
+            ],
+            "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",
+              "                            <div style=\"font-family: monospace; margin-bottom: 0.5rem\">\n",
+              "                                Running on <a href=${new URL(path, url).toString()} target=\"_blank\">\n",
+              "                                    https://localhost:${port}${path}\n",
+              "                                </a>\n",
+              "                            </div>\n",
+              "                        `;\n",
+              "                        element.appendChild(external_link);\n",
+              "\n",
+              "                        const iframe = document.createElement('iframe');\n",
+              "                        iframe.src = new URL(path, url).toString();\n",
+              "                        iframe.height = height;\n",
+              "                        iframe.allow = \"autoplay; camera; microphone; clipboard-read; clipboard-write;\"\n",
+              "                        iframe.width = width;\n",
+              "                        iframe.style.border = 0;\n",
+              "                        element.appendChild(iframe);\n",
+              "                    })(7860, \"/\", \"100%\", 500, false, window.element)"
+            ]
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": []
+          },
+          "metadata": {},
+          "execution_count": 5
+        }
+      ]
+    }
+  ]
+}