Datasets:
Tasks:
Audio Classification
Formats:
parquet
Sub-tasks:
keyword-spotting
Languages:
English
Size:
100K - 1M
ArXiv:
License:
Upload exploration.ipynb with huggingface_hub
Browse files- exploration.ipynb +410 -0
exploration.ipynb
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1 |
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{
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"cells": [
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"execution_count": 1,
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"id": "4991385a-1cc9-4cd7-b144-36dc0478fafe",
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"metadata": {},
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"outputs": [],
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"source": [
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"#!pip install renumics-spotlight datasets[audio]"
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]
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},
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"outputs": [],
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"source": [
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"import datasets\n",
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"from renumics import spotlight"
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]
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},
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"Downloading readme: 0%| | 0.00/782 [00:00<?, ?B/s]"
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"Generating test split: 0%| | 0/3081 [00:00<?, ? examples/s]"
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},
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"metadata": {},
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"output_type": "display_data"
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}
|
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],
|
157 |
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"source": [
|
158 |
+
"dataset = datasets.load_dataset(\"renumics/speech_commands_enrichment_only\")\n",
|
159 |
+
"raw_dataset = datasets.load_dataset(\"speech_commands\", 'v0.01')"
|
160 |
+
]
|
161 |
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},
|
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{
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"id": "7e486382-31cd-4b69-8a9e-fe3d7ac94b41",
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"metadata": {},
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"outputs": [
|
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{
|
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"data": {
|
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"text/plain": [
|
171 |
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"DatasetDict({\n",
|
172 |
+
" train: Dataset({\n",
|
173 |
+
" features: ['label_string', 'probability', 'probability_vector', 'prediction', 'prediction_string', 'embedding_reduced', '__index_level_0__'],\n",
|
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+
" num_rows: 51093\n",
|
175 |
+
" })\n",
|
176 |
+
" validation: Dataset({\n",
|
177 |
+
" features: ['label_string', 'probability', 'probability_vector', 'prediction', 'prediction_string', 'embedding_reduced', '__index_level_0__'],\n",
|
178 |
+
" num_rows: 6799\n",
|
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+
" })\n",
|
180 |
+
" test: Dataset({\n",
|
181 |
+
" features: ['label_string', 'probability', 'probability_vector', 'prediction', 'prediction_string', 'embedding_reduced', '__index_level_0__'],\n",
|
182 |
+
" num_rows: 3081\n",
|
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" })\n",
|
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+
"})"
|
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]
|
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+
},
|
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"execution_count": 3,
|
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"metadata": {},
|
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"output_type": "execute_result"
|
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}
|
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],
|
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"source": [
|
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"dataset"
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]
|
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+
},
|
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+
{
|
197 |
+
"cell_type": "code",
|
198 |
+
"execution_count": 4,
|
199 |
+
"id": "9594c54a-c024-4492-af7b-f1c25bb4de6b",
|
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"metadata": {},
|
201 |
+
"outputs": [
|
202 |
+
{
|
203 |
+
"data": {
|
204 |
+
"text/plain": [
|
205 |
+
"DatasetDict({\n",
|
206 |
+
" train: Dataset({\n",
|
207 |
+
" features: ['file', 'audio', 'label', 'is_unknown', 'speaker_id', 'utterance_id'],\n",
|
208 |
+
" num_rows: 51093\n",
|
209 |
+
" })\n",
|
210 |
+
" validation: Dataset({\n",
|
211 |
+
" features: ['file', 'audio', 'label', 'is_unknown', 'speaker_id', 'utterance_id'],\n",
|
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+
" num_rows: 6799\n",
|
213 |
+
" })\n",
|
214 |
+
" test: Dataset({\n",
|
215 |
+
" features: ['file', 'audio', 'label', 'is_unknown', 'speaker_id', 'utterance_id'],\n",
|
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+
" num_rows: 3081\n",
|
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+
" })\n",
|
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"})"
|
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]
|
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},
|
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"execution_count": 4,
|
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"metadata": {},
|
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"output_type": "execute_result"
|
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}
|
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],
|
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"source": [
|
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+
"raw_dataset"
|
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]
|
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},
|
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{
|
231 |
+
"cell_type": "code",
|
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+
"execution_count": 5,
|
233 |
+
"id": "ddda31eb-fdab-4ed3-81cc-88506ae0d7d5",
|
234 |
+
"metadata": {},
|
235 |
+
"outputs": [],
|
236 |
+
"source": [
|
237 |
+
"joined_dataset_enrichment = datasets.concatenate_datasets([dataset[\"train\"], dataset[\"validation\"], dataset[\"test\"]])\n",
|
238 |
+
"raw_dataset_joined = datasets.concatenate_datasets([raw_dataset[\"train\"].sort(\"file\"), raw_dataset[\"validation\"].sort(\"file\"), \n",
|
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+
" raw_dataset[\"test\"].sort(\"file\")])"
|
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]
|
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},
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{
|
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"cell_type": "code",
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"execution_count": 6,
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"id": "2b8918a3-5037-4062-b9cd-40b4a8a4d6c0",
|
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"metadata": {},
|
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"outputs": [
|
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{
|
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"data": {
|
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"text/plain": [
|
251 |
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"Dataset({\n",
|
252 |
+
" features: ['label_string', 'probability', 'probability_vector', 'prediction', 'prediction_string', 'embedding_reduced', '__index_level_0__'],\n",
|
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" num_rows: 60973\n",
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"})"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
|
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"joined_dataset_enrichment"
|
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "fa6ca118-3df0-4b6b-a036-4c70544500e3",
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"metadata": {},
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"outputs": [
|
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{
|
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"data": {
|
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"text/plain": [
|
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"Dataset({\n",
|
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" features: ['file', 'audio', 'label', 'is_unknown', 'speaker_id', 'utterance_id'],\n",
|
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+
" num_rows: 60973\n",
|
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+
"})"
|
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+
]
|
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+
},
|
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+
"execution_count": 7,
|
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+
"metadata": {},
|
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+
"output_type": "execute_result"
|
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+
}
|
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+
],
|
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+
"source": [
|
287 |
+
"#raw_dataset_joined = raw_dataset_joined.sort(\"file\")\n",
|
288 |
+
"raw_dataset_joined"
|
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+
]
|
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+
},
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+
{
|
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+
"cell_type": "code",
|
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+
"execution_count": 8,
|
294 |
+
"id": "0a56d781-5b5c-4deb-aa4f-c9a1a96ac650",
|
295 |
+
"metadata": {},
|
296 |
+
"outputs": [
|
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+
{
|
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+
"data": {
|
299 |
+
"application/vnd.jupyter.widget-view+json": {
|
300 |
+
"model_id": "4daa94720e334ecd9c1d3cc679bc1ee5",
|
301 |
+
"version_major": 2,
|
302 |
+
"version_minor": 0
|
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+
},
|
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+
"text/plain": [
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+
"Flattening the indices: 0%| | 0/60973 [00:00<?, ? examples/s]"
|
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+
]
|
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+
},
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"metadata": {},
|
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+
"output_type": "display_data"
|
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+
},
|
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+
{
|
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+
"data": {
|
313 |
+
"application/vnd.jupyter.widget-view+json": {
|
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+
"model_id": "5a7effce6372433b814701d1a0a51e05",
|
315 |
+
"version_major": 2,
|
316 |
+
"version_minor": 0
|
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+
},
|
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+
"text/plain": [
|
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+
"Flattening the indices: 0%| | 0/60973 [00:00<?, ? examples/s]"
|
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+
]
|
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+
},
|
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+
"metadata": {},
|
323 |
+
"output_type": "display_data"
|
324 |
+
}
|
325 |
+
],
|
326 |
+
"source": [
|
327 |
+
"complete_dataset = datasets.concatenate_datasets([raw_dataset_joined, joined_dataset_enrichment], axis=1)"
|
328 |
+
]
|
329 |
+
},
|
330 |
+
{
|
331 |
+
"cell_type": "code",
|
332 |
+
"execution_count": 9,
|
333 |
+
"id": "cb487431-8bc6-483a-bf25-a917278b6781",
|
334 |
+
"metadata": {},
|
335 |
+
"outputs": [
|
336 |
+
{
|
337 |
+
"data": {
|
338 |
+
"text/plain": [
|
339 |
+
"Dataset({\n",
|
340 |
+
" features: ['file', 'audio', 'label', 'is_unknown', 'speaker_id', 'utterance_id', 'label_string', 'probability', 'probability_vector', 'prediction', 'prediction_string', 'embedding_reduced', '__index_level_0__'],\n",
|
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+
" num_rows: 60973\n",
|
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+
"})"
|
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+
]
|
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+
},
|
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+
"execution_count": 9,
|
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+
"metadata": {},
|
347 |
+
"output_type": "execute_result"
|
348 |
+
}
|
349 |
+
],
|
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+
"source": [
|
351 |
+
"complete_dataset"
|
352 |
+
]
|
353 |
+
},
|
354 |
+
{
|
355 |
+
"cell_type": "code",
|
356 |
+
"execution_count": 11,
|
357 |
+
"id": "a11fefeb-9fd1-4500-9b9f-3275207b1cde",
|
358 |
+
"metadata": {},
|
359 |
+
"outputs": [
|
360 |
+
{
|
361 |
+
"name": "stderr",
|
362 |
+
"output_type": "stream",
|
363 |
+
"text": [
|
364 |
+
"\n",
|
365 |
+
"KeyboardInterrupt\n",
|
366 |
+
"\n"
|
367 |
+
]
|
368 |
+
}
|
369 |
+
],
|
370 |
+
"source": [
|
371 |
+
"spotlight.show(\n",
|
372 |
+
" complete_dataset,\n",
|
373 |
+
" #layout= layout.parse(\"spotlight-layout.json\"),\n",
|
374 |
+
" port=7860, \n",
|
375 |
+
" host=\"0.0.0.0\",\n",
|
376 |
+
" allow_filebrowsing=False \n",
|
377 |
+
" )"
|
378 |
+
]
|
379 |
+
},
|
380 |
+
{
|
381 |
+
"cell_type": "code",
|
382 |
+
"execution_count": null,
|
383 |
+
"id": "f1e38449-7bc1-4ae5-a754-a914a808a534",
|
384 |
+
"metadata": {},
|
385 |
+
"outputs": [],
|
386 |
+
"source": []
|
387 |
+
}
|
388 |
+
],
|
389 |
+
"metadata": {
|
390 |
+
"kernelspec": {
|
391 |
+
"display_name": "Python 3 (ipykernel)",
|
392 |
+
"language": "python",
|
393 |
+
"name": "python3"
|
394 |
+
},
|
395 |
+
"language_info": {
|
396 |
+
"codemirror_mode": {
|
397 |
+
"name": "ipython",
|
398 |
+
"version": 3
|
399 |
+
},
|
400 |
+
"file_extension": ".py",
|
401 |
+
"mimetype": "text/x-python",
|
402 |
+
"name": "python",
|
403 |
+
"nbconvert_exporter": "python",
|
404 |
+
"pygments_lexer": "ipython3",
|
405 |
+
"version": "3.10.12"
|
406 |
+
}
|
407 |
+
},
|
408 |
+
"nbformat": 4,
|
409 |
+
"nbformat_minor": 5
|
410 |
+
}
|