Fixing sentiment pipeline in 03-pipelines notebook.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
This commit is contained in:
Morgan Funtowicz
@@ -67,27 +67,16 @@
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},
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"cell_type": "code",
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"execution_count": 29,
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"execution_count": 6,
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"metadata": {
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"pycharm": {
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"is_executing": false,
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"name": "#%% code \n"
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}
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},
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"outputs": [
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{
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"ename": "SyntaxError",
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"evalue": "from __future__ imports must occur at the beginning of the file (<ipython-input-29-c3a037bd4c55>, line 5)",
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"output_type": "error",
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"traceback": [
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"\u001b[0;36m File \u001b[0;32m\"<ipython-input-29-c3a037bd4c55>\"\u001b[0;36m, line \u001b[0;32m5\u001b[0m\n\u001b[0;31m from transformers import pipeline\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m from __future__ imports must occur at the beginning of the file\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from __future__ import print_function\n",
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"from ipywidgets import interact, interactive, fixed, interact_manual\n",
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"import ipywidgets as widgets\n",
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"from transformers import pipeline"
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]
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@@ -105,7 +94,7 @@
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},
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 8,
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"is_executing": false,
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@@ -115,40 +104,35 @@
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"outputs": [
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"data": {
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"model_id": "6aeccfdf51994149bdd1f3d3533e380f",
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"version_major": 2,
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"version_minor": 0
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"HBox(children=(FloatProgress(value=0.0, description='Downloading', max=230.0, style=ProgressStyle(description_…"
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"version_minor": 0,
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"model_id": "c9db53f30b9446c0af03268633a966c0"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n"
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]
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"output_type": "stream"
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},
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{
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"data": {
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"text/plain": [
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"[{'label': 'POSITIVE', 'score': 0.800251},\n",
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" {'label': 'NEGATIVE', 'score': 1.2489903}]"
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]
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"text/plain": "[{'label': 'POSITIVE', 'score': 0.9997656}]"
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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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"output_type": "execute_result",
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"execution_count": 8
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}
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],
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"source": [
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"nlp_sentence_classif = pipeline('sentiment-analysis')\n",
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"nlp_sentence_classif(['Such a nice weather outside !', 'This movie was kind of boring.'])"
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"nlp_sentence_classif('Such a nice weather outside !')"
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]
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},
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{
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@@ -164,7 +148,7 @@
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"execution_count": 16,
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"execution_count": 9,
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"is_executing": false,
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@@ -174,40 +158,30 @@
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"outputs": [
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"version_minor": 0
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"model_id": "1e300789e22644f1aed66a5ed60e75c4"
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"metadata": {},
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"output_type": "display_data"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n"
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]
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],
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"output_type": "stream"
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},
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{
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"data": {
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"text/plain": [
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"[{'word': 'Hu', 'score': 0.9970937967300415, 'entity': 'I-ORG'},\n",
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" {'word': '##gging', 'score': 0.9345750212669373, 'entity': 'I-ORG'},\n",
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" {'word': 'Face', 'score': 0.9787060022354126, 'entity': 'I-ORG'},\n",
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" {'word': 'French', 'score': 0.9981995820999146, 'entity': 'I-MISC'},\n",
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" {'word': 'New', 'score': 0.9983047246932983, 'entity': 'I-LOC'},\n",
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" {'word': '-', 'score': 0.8913455009460449, 'entity': 'I-LOC'},\n",
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" {'word': 'York', 'score': 0.9979523420333862, 'entity': 'I-LOC'}]"
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]
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"text/plain": "[{'word': 'Hu', 'score': 0.9970937967300415, 'entity': 'I-ORG'},\n {'word': '##gging', 'score': 0.9345750212669373, 'entity': 'I-ORG'},\n {'word': 'Face', 'score': 0.9787060022354126, 'entity': 'I-ORG'},\n {'word': 'French', 'score': 0.9981995820999146, 'entity': 'I-MISC'},\n {'word': 'New', 'score': 0.9983047246932983, 'entity': 'I-LOC'},\n {'word': '-', 'score': 0.8913455009460449, 'entity': 'I-LOC'},\n {'word': 'York', 'score': 0.9979523420333862, 'entity': 'I-LOC'}]"
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},
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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"output_type": "execute_result",
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"source": [
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@@ -224,7 +198,7 @@
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"execution_count": 10,
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@@ -234,42 +208,38 @@
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"model_id": "82aca58f1ea24b4cb37f16402e8a5923"
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"\n"
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"convert squad examples to features: 100%|██████████| 1/1 [00:00<00:00, 53.05it/s]\n",
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"add example index and unique id: 100%|██████████| 1/1 [00:00<00:00, 2673.23it/s]\n"
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]
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"convert squad examples to features: 100%|██████████| 1/1 [00:00<00:00, 225.51it/s]\n",
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"add example index and unique id: 100%|██████████| 1/1 [00:00<00:00, 2158.67it/s]\n"
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"text/plain": [
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"{'score': 0.9632966867654424, 'start': 42, 'end': 50, 'answer': 'New-York.'}"
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"text/plain": "{'score': 0.9632966867654424, 'start': 42, 'end': 50, 'answer': 'New-York.'}"
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"execution_count": 18,
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@@ -286,7 +256,7 @@
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@@ -296,48 +266,30 @@
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"[{'sequence': '<s> Hugging Face is a French company based in Paris</s>',\n",
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" 'token': 2201},\n",
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" {'sequence': '<s> Hugging Face is a French company based in Lyon</s>',\n",
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" 'token': 12790},\n",
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" {'sequence': '<s> Hugging Face is a French company based in Brussels</s>',\n",
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" 'score': 0.055500105023384094,\n",
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" 'token': 6497},\n",
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" {'sequence': '<s> Hugging Face is a French company based in Geneva</s>',\n",
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" 'score': 0.04264815151691437,\n",
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" 'token': 11559},\n",
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" {'sequence': '<s> Hugging Face is a French company based in France</s>',\n",
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" 'score': 0.03868963569402695,\n",
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"text/plain": "[{'sequence': '<s> Hugging Face is a French company based in Paris</s>',\n 'score': 0.23106691241264343,\n 'token': 2201},\n {'sequence': '<s> Hugging Face is a French company based in Lyon</s>',\n 'score': 0.0819825753569603,\n 'token': 12790},\n {'sequence': '<s> Hugging Face is a French company based in Geneva</s>',\n 'score': 0.04769463092088699,\n 'token': 11559},\n {'sequence': '<s> Hugging Face is a French company based in Brussels</s>',\n 'score': 0.047622501850128174,\n 'token': 6497},\n {'sequence': '<s> Hugging Face is a French company based in France</s>',\n 'score': 0.04130595177412033,\n 'token': 1470}]"
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@@ -354,7 +306,7 @@
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@@ -364,34 +316,30 @@
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@@ -427,41 +375,27 @@
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"text": [
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"[{'word': 'Paris', 'score': 0.9991844296455383, 'entity': 'I-LOC'}]\n",
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"[{'sequence': '<s> I\\'m from Paris.\"</s>', 'score': 0.224044069647789, 'token': 72}, {'sequence': \"<s> I'm from Paris.)</s>\", 'score': 0.16959427297115326, 'token': 1592}, {'sequence': \"<s> I'm from Paris.]</s>\", 'score': 0.10994981974363327, 'token': 21838}, {'sequence': '<s> I\\'m from Paris!\"</s>', 'score': 0.0706234946846962, 'token': 2901}, {'sequence': \"<s> I'm from Paris.</s>\", 'score': 0.0698278620839119, 'token': 4}]\n",
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"[{'sequence': \"<s> I'm from Paris and London</s>\", 'score': 0.12238534539937973, 'token': 928}, {'sequence': \"<s> I'm from Paris and Brussels</s>\", 'score': 0.07107886672019958, 'token': 6497}, {'sequence': \"<s> I'm from Paris and Belgium</s>\", 'score': 0.040912602096796036, 'token': 7320}, {'sequence': \"<s> I'm from Paris and Berlin</s>\", 'score': 0.039884064346551895, 'token': 5459}, {'sequence': \"<s> I'm from Paris and Melbourne</s>\", 'score': 0.038133684545755386, 'token': 5703}]\n",
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"[{'sequence': '<s> I like go to sleep</s>', 'score': 0.08942786604166031, 'token': 3581}, {'sequence': '<s> I like go to bed</s>', 'score': 0.07789064943790436, 'token': 3267}, {'sequence': '<s> I like go to concerts</s>', 'score': 0.06356740742921829, 'token': 12858}, {'sequence': '<s> I like go to school</s>', 'score': 0.03660670667886734, 'token': 334}, {'sequence': '<s> I like go to dinner</s>', 'score': 0.032155368477106094, 'token': 3630}]\n"
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"source": [
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@@ -498,7 +432,7 @@
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"execution_count": 43,
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"execution_count": 14,
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@@ -508,46 +442,15 @@
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"data": {
|
||||
"text/plain": "Textarea(value='Einstein is famous for the general theory of relativity', description='Context:', placeholder=…",
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"model_id": "5ae68677bd8a41f990355aa43840d3f8",
|
||||
"version_major": 2,
|
||||
"version_minor": 0
|
||||
},
|
||||
"text/plain": [
|
||||
"Textarea(value='Einstein is famous for the general theory of relativity', description='Context:', placeholder=…"
|
||||
]
|
||||
"version_minor": 0,
|
||||
"model_id": "019fde2343634e94b6f32d04f6350ec1"
|
||||
}
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"application/vnd.jupyter.widget-view+json": {
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"model_id": "14bcfd9a2c5a47e6b1383989ab7632c8",
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||||
"version_major": 2,
|
||||
"version_minor": 0
|
||||
},
|
||||
"text/plain": [
|
||||
"Text(value='Why is Einstein famous for ?', description='Question:', placeholder='Enter something')"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"convert squad examples to features: 100%|██████████| 1/1 [00:00<00:00, 168.83it/s]\n",
|
||||
"add example index and unique id: 100%|██████████| 1/1 [00:00<00:00, 1919.59it/s]\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{'score': 0.40340670623875496, 'start': 27, 'end': 54, 'answer': 'general theory of relativity'}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
|
||||
Reference in New Issue
Block a user