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nazneen commited on Sep 24, 2022

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abe7f1c

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1 Parent(s): f357dd7

model usage

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Files changed (4) hide show

app.py +62 -0
assets/2021/model_init_time.csv +223 -0
assets/2022/model_init_time.csv +350 -0
requirements.txt +7 -0

app.py ADDED Viewed

	@@ -0,0 +1,62 @@

+## LIBRARIES ###
+from cProfile import label
+from tkinter import font
+from turtle import width
+import streamlit as st
+import pandas as pd
+from datetime import datetime
+import plotly.express as px
+def read_file_to_df(file):
+   return pd.read_csv(file)
+def date_range(df):
+    time = df.index.to_list()
+    time_range = []
+    for t in time:
+        time_range.append(str(datetime.strptime(t, '%Y-%m-%dT%H:%M:%S.%fZ').date().month) +'/' +  str(datetime.strptime(t, '%Y-%m-%dT%H:%M:%S.%fZ').date().day))
+    return time_range
+if __name__ == "__main__":
+    ### STREAMLIT APP CONGFIG ###
+    st.set_page_config(layout="wide", page_title="HF Hub Model Usage Visualization")
+    popularity = st.sidebar.radio(
+        "Model popularity", ('Low', 'Moderate', 'High'), key = "popularity", index=2)
+    st.header("Model Usage Visualization")
+    with st.container():
+        df_2021 = read_file_to_df("./assets/2021/model_init_time.csv")
+        df_2021.fillna(0, inplace=True)
+        df_plot = df_2021.set_index('Model').T
+        df_plot.index = date_range(df_plot)
+        df_plot_2021 = pd.DataFrame()
+        if popularity == 'Low':
+            df_plot_2021 = df_plot[df_plot.columns[(df_plot.mean(axis=0)<=5000) & (df_plot.mean(axis=0)>=3500)]]
+        elif popularity == 'Moderate':
+            df_plot_2021 =  df_plot[df_plot.columns[(df_plot.mean(axis=0)<=40000) & (df_plot.mean(axis=0)>=5000)]]
+        else:
+            df_plot_2021 = df_plot[df_plot.columns[df_plot.mean(axis=0)>=40000]]
+        fig = px.line(df_plot_2021, title="Model Usage Trends in 2021", labels={"index": "Weeks", "value": "Usage", "variable": "Model"})
+        st.plotly_chart(fig, use_container_width=True)
+    with st.container():
+        df_2022 = read_file_to_df("./assets/2022/model_init_time.csv")
+        df_2022.fillna(0, inplace=True)
+        df_plot = df_2022.set_index('Model').T
+        df_plot.index = date_range(df_plot)
+        df_plot_2022 = pd.DataFrame()
+        if popularity == 'Low':
+            df_plot_2022 = df_plot[df_plot.columns[(df_plot.mean(axis=0)<500) & (df_plot.mean(axis=0)>=300)]]
+        elif popularity == 'Moderate':
+            df_plot_2022 =  df_plot[df_plot.columns[(df_plot.mean(axis=0)<=1500) & (df_plot.mean(axis=0)>=500)]]
+        else:
+            df_plot_2022 = df_plot[df_plot.columns[df_plot.mean(axis=0)>=1500]]
+        fig = px.line(df_plot_2022, title="Model Usage Trends in 2022", labels={"index": "Weeks", "value": "Usage", "variable": "Model"})
+        st.plotly_chart(fig, use_container_width=True)

assets/2021/model_init_time.csv ADDED Viewed

	@@ -0,0 +1,223 @@

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+ismail-lucifer011/autotrain-company_all-903429548,,,,,,,,,94,67,18,48,49,0,14,4,12,17,16,6,10,2,6,25,32,3
+ai4bharat/IndicNER,,,,,,,,,,,,17,6,23,13,6,55,25,62,29,25,38,55,49,43,2
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+JeremiahZ/roberta-base-rte,,,,,,,,,,,,3,4,0,0,0,0,0,8,8,2,69,320,11,4,
+czearing/article-title-generator,,,,,,,,,,,,,,36,67,14,13,6,34,6,21,15,28,120,32,3
+Blaise-g/longt5_tglobal_large_sumpubmed,,,,,,,,,,,,,,,,,,,,2,124,38,16,34,15,
+JulesBelveze/t5-small-headline-generator,,,,,,,,,,,,,,11,11,14,33,14,40,35,4,22,8,72,34,2
+StanfordAIMI/stanford-deidentifier-only-i2b2,,,,,,,,,,,,,3,0,0,0,34,34,11,0,0,4,158,544,2,3
+StanfordAIMI/stanford-deidentifier-with-radiology-reports-and-i2b2,,,,,,,,,,,,,3,0,0,0,12,6,3,3,0,4,194,582,9,4
+KoichiYasuoka/deberta-base-japanese-wikipedia,,,,,,,,,,,,,21,25,7,8,2,1,4,0,4,9,0,40,94,9
+hf-internal-testing/tiny-random-bloom,,,,,,,,,,,,,,,6,8,10,0,107,1,32,7,1,4,28,3
+StanfordAIMI/stanford-deidentifier-only-radiology-reports-augmented,,,,,,,,,,,,,3,0,0,0,49,15,16,6,3,0,129,536,2,1
+aniketface/DialoGPT-medium-elon,,,,,,,,,,,,,,,,,,,,84,193,106,12,13,5,
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+Blaise-g/led_pubmed_sumpubmed_1,,,,,,,,,,,,,,,,,,,10,17,33,15,0,97,80,2
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+stanford-oval/paraphraser-bart-large,,,,,,,,,,,,,,,,,,,,31,33,0,33,107,42,3
+IDEA-CCNL/Randeng-Pegasus-238M-Chinese,,,,,,,,,,,,,,12,14,45,1,5,7,11,9,9,29,42,13,8
+clearspandex/face-parsing,,,,,,,,,,,,,,,67,18,16,13,31,23,32,6,13,37,40,2
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+Jinchen/roberta-base-finetuned-mrpc,,,,,,,,,,,,,,,,20,4,0,9,0,0,2,313,,,
+StanfordAIMI/stanford-deidentifier-only-radiology-reports,,,,,,,,,,,,,3,0,0,0,4,2,5,6,0,1,121,531,2,1
+SoDehghan/supmpn-bert-base-uncased,,,,,,,,,,2,15,0,33,66,0,0,0,0,0,0,0,4,0,59,,
+fabianmmueller/deep-haiku-gpt-2,,,,,,,,,21,0,0,5,22,29,0,0,9,0,3,16,3,0,6,22,79,
+tmills/clinical_tempeval_pubmedbert,,,,,,,,,19,1,7,0,0,0,0,0,0,0,0,0,1,1,0,1,86,37
+inigopm/beto-base-spanish-squades2,,,,,,,,,,,,,,,11,9,4,3,9,37,16,21,3,27,55,2
+projecte-aina/roberta-base-ca-v2-cased-pos,,,,,,,,,,,,,,,,,7,0,0,0,89,17,32,5,2,1
+yanaiela/roberta-base-epoch_83,,,,,,,,,,,,,,,,,,6,9,0,3,2,76,113,89,
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+ml6team/keyphrase-extraction-kbir-semeval2017,,,,,,,,,,,,3,6,0,2,2,7,6,1,6,7,5,5,73,10,1
+Lexemo/roberta_large_legal_act_extraction,,,,,,,,,,,,,62,3,25,6,3,11,6,25,3,17,9,0,14,2
+Yuetian/T5-finetuned-storyCommonsense,,,,,,,,,,,,,,,,,,15,44,31,22,6,3,0,9,
+apple/deeplabv3-mobilevit-x-small,,,,,,,,,,2,2,1,2,2,11,6,7,1,6,1,13,40,25,4,9,6
+tner/roberta-large-bc5cdr,,,,,,,,,,,,,,,,,,,,4,2,0,0,97,9,5
+ccdv/lsg-distilcamembert-base-4096,,,3,40,0,0,3,0,5,47,4,0,0,2,0,0,0,0,0,1,0,0,0,90,63,
+tner/roberta-large-wnut2017,,,,,,,,,,,,,,,,,,,,27,30,0,7,15,19,14
+codeparrot/codeparrot-small-text-to-code,,,,,,,,,,,,,,,,10,28,10,15,38,13,5,8,15,6,1
+SamuelYang/SentMAE,,,,,,,,,,,,,,,,,,,,87,49,61,75,154,42,
+simecek/DNADebertaK6b,,,,,,,,,,,,,,,,,,,,8,11,0,0,3,67,2
+vishw2703/unisumm_3,,,,,,,,,,,,,,,,,,,5,74,9,1,36,20,1,4
+ZakaryaRouzki/t5-punctuation,,,,,,,,,,,,,,38,4,9,3,6,9,6,13,16,21,16,3,
+diversifix/diversiformer,,,,,,,,,,,,66,25,14,9,24,0,0,0,5,0,0,13,115,1,
+IDEA-CCNL/Erlangshen-ZEN2-668M-Chinese,,,,,,,,,,,,,,,,,,2,1,0,0,117,0,3,,
+ckiplab/bert-base-han-chinese,,,,,,,,,,,,,,,27,3,3,15,0,3,5,4,0,6,1,37
+abdulmatinomotoso/t5_large_headline_generator_testing_3,,,,,,,,,,,,,,,,,,3,3,8,0,0,39,8,55,2
+autoevaluate/roberta-base-squad2,,,,,,,,,,,,,,,,,36,0,9,3,1,2,36,0,2,
+RVN/BERTovski,,,,,,,,,,,,,,,,,,,,6,0,29,15,22,7,
+Mithil/86RecallRoberta,,,,,,,,,,,,,,,62,4,0,1,8,0,0,5,0,36,,
+embedding-data/distilroberta-base-sentence-transformer,,,,,,,,,,,,,,,,,,,6,6,6,3,7,11,21,10
+kalpeshk2011/rankgen-t5-xl-pg19,,,,,,,,,,,,,,,,,2,0,0,0,5,1,603,0,207,400
+ridhoalattqas/xlrs-best-lm,,,,,,,,,,,56,0,2,0,15,12,1,8,6,6,11,0,0,5,0,2
+RUCAIBox/mvp-story,,,,,,,,,,2,0,0,2,1,0,0,13,3,0,5,0,7,3,47,7,2
+abdulmatinomotoso/t5_large_headline_generator_testing_1,,,,,,,,,,,,,,,,,,12,0,3,0,10,48,0,1,
+McGill-NLP/roberta-large-faithcritic,,,,,,,,,,,,,,,,,,30,12,3,3,3,6,31,4,1
+kalpeshk2011/rankgen-t5-large-all,,,,,,,,,,,,,,,,,3,0,0,0,0,3,502,0,220,208
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+AkashKhamkar/InSumT510k,,,,,,,,,,,,,,,,,,,,68,18,5,3,,,
+Gorilla115/t5-shakespearify-lite,,,,,,,,,,,,,,,,,,,,22,30,13,6,6,3,7
+MCG-NJU/videomae-base-short,,,,,,,,,,,,,,,,,,,44,24,0,1,0,1,1,
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+SafiUllahShahid/EnGECmodel,,,,,,,,,,,,,,,,,,3,2,6,8,29,1,4,,
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+AIRI-Institute/gena-lm-bert-base,,,,,,,,,,,,,2,2,6,1,1,0,4,0,3,11,2,4,,
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+ccdv/lsg-camembert-base-4096,,,,,,,,,,,,,,,,,,5,0,0,0,0,0,122,64,
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+alk/roberta-large-mnli-finetuned-header-classifier,,,,,,,,,,,,,,5,9,0,0,0,3,0,3,0,0,0,4,2
+TheDiamondKing/Discord-Message-Small,,,,,,,,,,,,,,9,3,0,0,3,0,0,6,3,0,0,2,
+HUPD/hupd-distilroberta-base,,,,,,,,,,,,,,,,,,,,5,0,0,0,0,9,
+ccdv/lsg-albert-base-v2-4096,,,,,,,,,,,,,,,,,,3,0,1,0,0,0,54,30,
+pyronear/rexnet1_3x,,,,,,,,,,,,,,,,2,0,0,0,0,1,0,2,2,2,
+MCG-NJU/videomae-base-ssv2,,,,,,,,,,,,,,,,,,,2,0,0,0,0,2,2,
+ArthurZ/tiny-random-bert-sharded,,,,,,,,,,,,1,,,,,,,,,,,,,,

requirements.txt ADDED Viewed

	@@ -0,0 +1,7 @@

+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: osx-arm64
+pandas==1.3.4
+streamlit-vega-lite==0.1.0
+streamlit==1.2.0
+plotly=5.10.0=pypi_0