Upload Copy_of_demo.ipynb
Browse files- Copy_of_demo.ipynb +1389 -0
Copy_of_demo.ipynb
ADDED
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.9/71.9 kB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m53.6/53.6 kB\u001b[0m \u001b[31m3.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m307.7/307.7 kB\u001b[0m \u001b[31m17.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m341.4/341.4 kB\u001b[0m \u001b[31m28.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.4/3.4 MB\u001b[0m \u001b[31m60.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.2/1.2 MB\u001b[0m \u001b[31m45.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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"\u001b[?25h Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
|
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+
]
|
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+
}
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+
],
|
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"source": [
|
1084 |
+
"!pip install gradio --quiet\n",
|
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+
"!pip install transformers --quiet\n"
|
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+
]
|
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+
},
|
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+
{
|
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+
"cell_type": "code",
|
1090 |
+
"source": [
|
1091 |
+
"# Use a pipeline as a high-level helper\n",
|
1092 |
+
"from transformers import pipeline\n",
|
1093 |
+
"\n",
|
1094 |
+
"sentiment_analysis = pipeline(\"text-classification\", model=\"avichr/heBERT_sentiment_analysis\")\n",
|
1095 |
+
"def analyze_sentiment(text):\n",
|
1096 |
+
" results = sentiment_analysis(text)\n",
|
1097 |
+
" for result in results:\n",
|
1098 |
+
" print(f\"Label: {result['label']}, Score: {result['score']}\")\n"
|
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+
],
|
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+
"metadata": {
|
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"colab": {
|
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"base_uri": "https://localhost:8080/",
|
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"height": 113,
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"referenced_widgets": [
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"548aad754b6e4c6a985a0ff92d600e49",
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"86744b71c3c14bcfb9d6b02b2ddf444c",
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"56ee1264d8ef428e9ff8fdd16d3675a9",
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"d485adb6269b4faf978f3cad9555885a",
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"e7b2a3cf5b4b47e4959ccdbaf392a19c",
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"df3449dc4fa845718559b5c05cf4ea17",
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"e6dc642105de42469aff81b691f149ea",
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"7335cf52355943a1a06a1bc861958d66",
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"f123029dde99458eb0b03840fb73db40",
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"a0bad14b95d843659cb3b65d3a1ff98f",
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"fea405f7532b4226b3cff52c32a719dd",
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"7368f4df9fc34620b614a72987ae2804",
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|
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]
|
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},
|
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"id": "Q5loU2HPrUEe",
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"outputId": "6aa6b151-697e-4f3b-f4c8-7cb1582b3963"
|
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},
|
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"execution_count": null,
|
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"outputs": [
|
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{
|
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"output_type": "display_data",
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"version_major": 2,
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"version_minor": 0,
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|
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}
|
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},
|
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"metadata": {}
|
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},
|
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{
|
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"output_type": "display_data",
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"version_major": 2,
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"model_id": "988c1301b1134f50aae335a84aac12de"
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}
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},
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"metadata": {}
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},
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{
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"output_type": "display_data",
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"version_major": 2,
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"version_minor": 0,
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"model_id": "a32440921c01484a82221926be99daad"
|
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}
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},
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"metadata": {}
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},
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{
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"cell_type": "code",
|
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"source": [
|
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+
"texts = [\n",
|
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+
" \"Worst rental I ever got\"\n",
|
1194 |
+
" \"I really enjoyed my stay !\"\n",
|
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+
"\n",
|
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+
"]"
|
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+
],
|
1198 |
+
"metadata": {
|
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"id": "XwVzVFQNts5W"
|
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},
|
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"execution_count": null,
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"outputs": []
|
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+
},
|
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+
{
|
1205 |
+
"cell_type": "code",
|
1206 |
+
"source": [
|
1207 |
+
"analyze_sentiment(texts)"
|
1208 |
+
],
|
1209 |
+
"metadata": {
|
1210 |
+
"colab": {
|
1211 |
+
"base_uri": "https://localhost:8080/"
|
1212 |
+
},
|
1213 |
+
"id": "xCXncnWetxtz",
|
1214 |
+
"outputId": "0f00df07-8f93-43af-cad8-9837b7800b9e"
|
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+
},
|
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+
"execution_count": null,
|
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+
"outputs": [
|
1218 |
+
{
|
1219 |
+
"output_type": "stream",
|
1220 |
+
"name": "stdout",
|
1221 |
+
"text": [
|
1222 |
+
"Label: positive, Score: 0.9959390163421631\n"
|
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+
]
|
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+
}
|
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]
|
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},
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{
|
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"cell_type": "code",
|
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"source": [
|
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+
"!pip install gradio\n"
|
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],
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"metadata": {
|
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"colab": {
|
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"base_uri": "https://localhost:8080/"
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},
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"id": "K5-1OZWoxLs2",
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"outputId": "c5d0cbd6-77a8-46e3-b8e4-cdbf0707a071"
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},
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"execution_count": null,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Requirement already satisfied: gradio in /usr/local/lib/python3.10/dist-packages (4.37.2)\n",
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"Requirement already satisfied: aiofiles<24.0,>=22.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (23.2.1)\n",
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"Requirement already satisfied: altair<6.0,>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (4.2.2)\n",
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"Requirement already satisfied: fastapi in /usr/local/lib/python3.10/dist-packages (from gradio) (0.111.0)\n",
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"Requirement already satisfied: ffmpy in /usr/local/lib/python3.10/dist-packages (from gradio) (0.3.2)\n",
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"Requirement already satisfied: gradio-client==1.0.2 in /usr/local/lib/python3.10/dist-packages (from gradio) (1.0.2)\n",
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"Requirement already satisfied: httpx>=0.24.1 in /usr/local/lib/python3.10/dist-packages (from gradio) (0.27.0)\n",
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"Requirement already satisfied: huggingface-hub>=0.19.3 in /usr/local/lib/python3.10/dist-packages (from gradio) (0.23.4)\n",
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"Requirement already satisfied: importlib-resources<7.0,>=1.3 in /usr/local/lib/python3.10/dist-packages (from gradio) (6.4.0)\n",
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"Requirement already satisfied: pandas<3.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (2.0.3)\n",
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"Requirement already satisfied: pillow<11.0,>=8.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (9.4.0)\n",
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"Requirement already satisfied: email_validator>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from fastapi->gradio) (2.2.0)\n",
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]
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}
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]
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},
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{
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"cell_type": "code",
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"source": [
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"import gradio as gr\n",
|
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"from transformers import pipeline\n",
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"\n",
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"\n",
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"\n",
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"interface = gr.Interface(\n",
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" fn=analyze_sentiment,\n",
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" inputs=gr.Textbox(lines=2, placeholder=\"Enter your review or statement here...\"),\n",
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" outputs=[\n",
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" gr.Textbox(label=\"Sentiment\"),\n",
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" gr.Number(label=\"Score\")\n",
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+
" ],\n",
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+
" title=\"Sentiment Analysis Score\"\n",
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+
")\n",
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"\n",
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"\n",
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"interface.launch()\n"
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+
],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 645
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},
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"id": "h33cqWaUy51M",
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"outputId": "df32b15e-8160-48ef-bbfc-91abcd4dd402"
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+
},
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+
"execution_count": null,
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"outputs": [
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+
{
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+
"output_type": "stream",
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+
"name": "stdout",
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"text": [
|
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+
"Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
|
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+
"\n",
|
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+
"Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
|
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+
"Running on public URL: https://cf181fb2245157498a.gradio.live\n",
|
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+
"\n",
|
1363 |
+
"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
|
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+
]
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+
},
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{
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"output_type": "display_data",
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"data": {
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"text/plain": [
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"<IPython.core.display.HTML object>"
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],
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"text/html": [
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"<div><iframe src=\"https://cf181fb2245157498a.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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]
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},
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"metadata": {}
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},
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{
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"output_type": "execute_result",
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"data": {
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"text/plain": []
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},
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"metadata": {},
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"execution_count": 14
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}
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]
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}
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]
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}
|