Spaces:
Runtime error
Runtime error
Sasha
commited on
Commit
•
9c420d3
1
Parent(s):
95b75a7
Cleaning things up a bit
Browse files- data/carbon_df.pkl +0 -0
- hf-earth.png +0 -0
- notebooks/APICarbonQuery.ipynb +200 -0
data/carbon_df.pkl
ADDED
Binary file (7.32 kB). View file
|
|
hf-earth.png
ADDED
![]() |
notebooks/APICarbonQuery.ipynb
ADDED
@@ -0,0 +1,200 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"cells": [
|
3 |
+
{
|
4 |
+
"cell_type": "code",
|
5 |
+
"execution_count": 1,
|
6 |
+
"id": "c82eb8a8",
|
7 |
+
"metadata": {},
|
8 |
+
"outputs": [],
|
9 |
+
"source": [
|
10 |
+
"import json, requests, urllib"
|
11 |
+
]
|
12 |
+
},
|
13 |
+
{
|
14 |
+
"cell_type": "code",
|
15 |
+
"execution_count": 2,
|
16 |
+
"id": "45a53227",
|
17 |
+
"metadata": {},
|
18 |
+
"outputs": [],
|
19 |
+
"source": [
|
20 |
+
"import pandas as pd"
|
21 |
+
]
|
22 |
+
},
|
23 |
+
{
|
24 |
+
"cell_type": "code",
|
25 |
+
"execution_count": 3,
|
26 |
+
"id": "5ee17bd2",
|
27 |
+
"metadata": {},
|
28 |
+
"outputs": [],
|
29 |
+
"source": [
|
30 |
+
"response = requests.get(\"https://huggingface.co/api/models?filter=co2_eq_emissions\")"
|
31 |
+
]
|
32 |
+
},
|
33 |
+
{
|
34 |
+
"cell_type": "code",
|
35 |
+
"execution_count": 4,
|
36 |
+
"id": "805a29d7",
|
37 |
+
"metadata": {},
|
38 |
+
"outputs": [
|
39 |
+
{
|
40 |
+
"name": "stdout",
|
41 |
+
"output_type": "stream",
|
42 |
+
"text": [
|
43 |
+
"Out of 78 models, 78 of them reported carbon emissions\n"
|
44 |
+
]
|
45 |
+
}
|
46 |
+
],
|
47 |
+
"source": [
|
48 |
+
"modelcount=0\n",
|
49 |
+
"carboncount=0\n",
|
50 |
+
"\n",
|
51 |
+
"carbon_df = pd.DataFrame(columns=['name','task','carbon'])\n",
|
52 |
+
"\n",
|
53 |
+
"for model in response.json():\n",
|
54 |
+
" modelcount+=1\n",
|
55 |
+
" if model['private'] == False:\n",
|
56 |
+
" try:\n",
|
57 |
+
" readme = urllib.request.urlopen(\"https://huggingface.co/\"+model['modelId']+\"/raw/main/README.md\")\n",
|
58 |
+
" for line in readme:\n",
|
59 |
+
" decoded_line = line.decode(\"utf-8\")\n",
|
60 |
+
" if 'co2_eq_emissions' in decoded_line:\n",
|
61 |
+
" carboncount+=1\n",
|
62 |
+
" #print(model['modelId'], model['pipeline_tag'], decoded_line.split(\":\")[1])\n",
|
63 |
+
" try:\n",
|
64 |
+
" carbon_df.at[carboncount,'name'] = str(model['modelId'])\n",
|
65 |
+
" carbon_df.at[carboncount,'task'] = str(model['pipeline_tag'])\n",
|
66 |
+
" carbon_df.at[carboncount,'carbon'] = float(decoded_line.split(\":\")[1].replace('\\n',''))\n",
|
67 |
+
" except:\n",
|
68 |
+
" carbon_df.at[carboncount,'name'] = str(model['modelId'])\n",
|
69 |
+
" carbon_df.at[carboncount,'task'] = ''\n",
|
70 |
+
" carbon_df.at[carboncount,'carbon'] = float(decoded_line.split(\":\")[1].replace('\\n',''))\n",
|
71 |
+
" except:\n",
|
72 |
+
" continue\n",
|
73 |
+
"print(\"Out of \"+str(modelcount)+\" models, \"+str(carboncount)+ \" of them reported carbon emissions\")"
|
74 |
+
]
|
75 |
+
},
|
76 |
+
{
|
77 |
+
"cell_type": "code",
|
78 |
+
"execution_count": 5,
|
79 |
+
"id": "ce21fde5",
|
80 |
+
"metadata": {},
|
81 |
+
"outputs": [
|
82 |
+
{
|
83 |
+
"data": {
|
84 |
+
"text/html": [
|
85 |
+
"<div>\n",
|
86 |
+
"<style scoped>\n",
|
87 |
+
" .dataframe tbody tr th:only-of-type {\n",
|
88 |
+
" vertical-align: middle;\n",
|
89 |
+
" }\n",
|
90 |
+
"\n",
|
91 |
+
" .dataframe tbody tr th {\n",
|
92 |
+
" vertical-align: top;\n",
|
93 |
+
" }\n",
|
94 |
+
"\n",
|
95 |
+
" .dataframe thead th {\n",
|
96 |
+
" text-align: right;\n",
|
97 |
+
" }\n",
|
98 |
+
"</style>\n",
|
99 |
+
"<table border=\"1\" class=\"dataframe\">\n",
|
100 |
+
" <thead>\n",
|
101 |
+
" <tr style=\"text-align: right;\">\n",
|
102 |
+
" <th></th>\n",
|
103 |
+
" <th>name</th>\n",
|
104 |
+
" <th>task</th>\n",
|
105 |
+
" <th>carbon</th>\n",
|
106 |
+
" </tr>\n",
|
107 |
+
" </thead>\n",
|
108 |
+
" <tbody>\n",
|
109 |
+
" <tr>\n",
|
110 |
+
" <th>1</th>\n",
|
111 |
+
" <td>Aimendo/autonlp-triage-35248482</td>\n",
|
112 |
+
" <td>text-classification</td>\n",
|
113 |
+
" <td>7.989145</td>\n",
|
114 |
+
" </tr>\n",
|
115 |
+
" <tr>\n",
|
116 |
+
" <th>2</th>\n",
|
117 |
+
" <td>Anorak/nirvana</td>\n",
|
118 |
+
" <td>text2text-generation</td>\n",
|
119 |
+
" <td>4.214013</td>\n",
|
120 |
+
" </tr>\n",
|
121 |
+
" <tr>\n",
|
122 |
+
" <th>3</th>\n",
|
123 |
+
" <td>AryanLala/autonlp-Scientific_Title_Generator-3...</td>\n",
|
124 |
+
" <td>text2text-generation</td>\n",
|
125 |
+
" <td>137.605741</td>\n",
|
126 |
+
" </tr>\n",
|
127 |
+
" <tr>\n",
|
128 |
+
" <th>4</th>\n",
|
129 |
+
" <td>Crasher222/kaggle-comp-test</td>\n",
|
130 |
+
" <td>text-classification</td>\n",
|
131 |
+
" <td>60.744727</td>\n",
|
132 |
+
" </tr>\n",
|
133 |
+
" <tr>\n",
|
134 |
+
" <th>5</th>\n",
|
135 |
+
" <td>Emanuel/autonlp-pos-tag-bosque</td>\n",
|
136 |
+
" <td>token-classification</td>\n",
|
137 |
+
" <td>6.210727</td>\n",
|
138 |
+
" </tr>\n",
|
139 |
+
" </tbody>\n",
|
140 |
+
"</table>\n",
|
141 |
+
"</div>"
|
142 |
+
],
|
143 |
+
"text/plain": [
|
144 |
+
" name task \\\n",
|
145 |
+
"1 Aimendo/autonlp-triage-35248482 text-classification \n",
|
146 |
+
"2 Anorak/nirvana text2text-generation \n",
|
147 |
+
"3 AryanLala/autonlp-Scientific_Title_Generator-3... text2text-generation \n",
|
148 |
+
"4 Crasher222/kaggle-comp-test text-classification \n",
|
149 |
+
"5 Emanuel/autonlp-pos-tag-bosque token-classification \n",
|
150 |
+
"\n",
|
151 |
+
" carbon \n",
|
152 |
+
"1 7.989145 \n",
|
153 |
+
"2 4.214013 \n",
|
154 |
+
"3 137.605741 \n",
|
155 |
+
"4 60.744727 \n",
|
156 |
+
"5 6.210727 "
|
157 |
+
]
|
158 |
+
},
|
159 |
+
"execution_count": 5,
|
160 |
+
"metadata": {},
|
161 |
+
"output_type": "execute_result"
|
162 |
+
}
|
163 |
+
],
|
164 |
+
"source": [
|
165 |
+
"carbon_df.head()"
|
166 |
+
]
|
167 |
+
},
|
168 |
+
{
|
169 |
+
"cell_type": "code",
|
170 |
+
"execution_count": 11,
|
171 |
+
"id": "fe01a841",
|
172 |
+
"metadata": {},
|
173 |
+
"outputs": [],
|
174 |
+
"source": [
|
175 |
+
"carbon_df.to_pickle(\"./carbon_df.pkl\")"
|
176 |
+
]
|
177 |
+
}
|
178 |
+
],
|
179 |
+
"metadata": {
|
180 |
+
"kernelspec": {
|
181 |
+
"display_name": "datametrics",
|
182 |
+
"language": "python",
|
183 |
+
"name": "datametrics"
|
184 |
+
},
|
185 |
+
"language_info": {
|
186 |
+
"codemirror_mode": {
|
187 |
+
"name": "ipython",
|
188 |
+
"version": 3
|
189 |
+
},
|
190 |
+
"file_extension": ".py",
|
191 |
+
"mimetype": "text/x-python",
|
192 |
+
"name": "python",
|
193 |
+
"nbconvert_exporter": "python",
|
194 |
+
"pygments_lexer": "ipython3",
|
195 |
+
"version": "3.8.2"
|
196 |
+
}
|
197 |
+
},
|
198 |
+
"nbformat": 4,
|
199 |
+
"nbformat_minor": 5
|
200 |
+
}
|