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update hf_compare notebook
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‎notebooks/hf_compare.ipynb‎

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@@ -187,7 +187,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "2ffb58863ba0436296433ed981dc49db",
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"model_id": "e21c690b98854a098fc213c986cdae58",
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"version_major": 2,
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"version_minor": 0
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},
@@ -261,8 +261,8 @@
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" translated_texts = list()\n",
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" for batch in get_batches(texts,batch_size=model.generation_config.batch_size):\n",
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" translated_tokens = model.generate(\n",
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" top_k=10,\n",
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" top_p=0.75,\n",
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" top_k=100,\n",
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" top_p=0.8,\n",
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" do_sample=True,\n",
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" temperature=0.9,\n",
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" **tokenizer(batch, return_tensors=\"pt\",padding=True),\n",
@@ -279,7 +279,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "a27619cff1ed4b7bb054e45a9df98465",
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"version_major": 2,
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"version_minor": 0
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},
@@ -315,15 +315,15 @@
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{
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"text/plain": [
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" 'counts': [132, 60, 31, 14],\n",
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" 'totals': [277, 267, 257, 248],\n",
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" 'precisions': [47.65342960288809,\n",
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" 'bp': 1.0,\n",
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" 'sys_len': 277,\n",
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" 'ref_len': 272}"
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]
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},
@@ -377,7 +377,7 @@
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{
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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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},
@@ -451,8 +451,8 @@
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" translated_texts = list()\n",
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" for batch in get_batches(texts,batch_size=model.generation_config.batch_size):\n",
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" translated_tokens = model.generate(\n",
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" top_k=10,\n",
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" top_p=0.75,\n",
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" top_k=100,\n",
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" top_p=0.8,\n",
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" num_beams=4,\n",
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" do_sample=True,\n",
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" temperature=0.9,\n",
@@ -471,7 +471,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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@@ -507,13 +507,13 @@
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{
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"data": {
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"{'score': 21.323465966136123,\n",
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" 'counts': [135, 69, 42, 25],\n",
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" 'totals': [262, 252, 242, 233],\n",
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" 'precisions': [51.52671755725191,\n",
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" 10.729613733905579],\n",
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" 'bp': 0.9625512774839297,\n",
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" 'sys_len': 262,\n",
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" 'ref_len': 272}"
@@ -653,7 +653,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "d0101acb14924ebc9b74f899d1a28095",
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"version_major": 2,
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@@ -719,16 +719,16 @@
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"execution_count": 36,
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"metadata": {},
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"outputs": [],
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"source": [
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"greedy_sequences_generator = GreedyGenerator(\n",
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" use_tqdm=True,\n",
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" temperature=0.9,\n",
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" top_k_sampling=10,\n",
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" sort_samples=True,\n",
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" top_p_sampling=0.75,\n",
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" top_k_sampling=100,\n",
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" top_p_sampling=0.8,\n",
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" device=model.device,\n",
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" multinomial_sampling=True,\n",
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" generation_forward=generate,\n",
@@ -741,13 +741,13 @@
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"execution_count": 37,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"version_major": 2,
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},
@@ -764,7 +764,7 @@
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"(10, 10, 10)"
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]
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},
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"execution_count": 25,
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"execution_count": 37,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -777,25 +777,22 @@
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"execution_count": 38,
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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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"{'score': 9.729423488181931,\n",
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" 'counts': [109, 47, 19, 4],\n",
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" 'sys_len': 266,\n",
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"{'score': 16.963549254009152,\n",
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" 'counts': [133, 61, 31, 16],\n",
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" 'totals': [279, 269, 259, 250],\n",
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" 'precisions': [47.67025089605735, 22.676579925650557, 11.96911196911197, 6.4],\n",
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" 'bp': 1.0,\n",
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" 'sys_len': 279,\n",
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" 'ref_len': 272}"
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]
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},
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"execution_count": 38,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -839,7 +836,7 @@
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{
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"data": {
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},
@@ -905,7 +902,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"execution_count": 33,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -914,9 +911,9 @@
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" use_tqdm=True,\n",
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" temperature=0.9,\n",
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" sort_samples=True,\n",
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" top_k_sampling=10,\n",
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" top_k_sampling=100,\n",
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" length_penalty=0.6,\n",
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" top_p_sampling=0.75,\n",
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" top_p_sampling=0.8,\n",
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" device=model.device,\n",
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" multinomial_sampling=True,\n",
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" generation_forward=generate,\n",
@@ -929,13 +926,13 @@
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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"execution_count": 34,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"version_major": 2,
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"version_minor": 0
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},
@@ -952,7 +949,7 @@
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"(10, 10, 10)"
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]
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},
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"execution_count": 31,
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"execution_count": 34,
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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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{
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"cell_type": "code",
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"execution_count": 32,
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"execution_count": 35,
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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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"{'score': 20.27713611022614,\n",
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" 'sys_len': 260,\n",
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" 'ref_len': 272}"
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]
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},
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"execution_count": 35,
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"metadata": {},
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"output_type": "execute_result"
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}

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