Spaces:
Runtime error
Runtime error
Update curated.py
Browse files- curated.py +363 -13
curated.py
CHANGED
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@@ -74,7 +74,7 @@ wikipedia_filter = pd.DataFrame(
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"Percent Removed After Unigram Probability Filter": [
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"0.00%",
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],
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-
"
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"",
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],
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"Total Percentage Remaining": [
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@@ -86,6 +86,356 @@ wikipedia_filter = pd.DataFrame(
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table_html_wikipedia = wikipedia_filter.to_html(index=False, border=0)
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table_div_wikipedia = Div(NotStr(table_html_wikipedia), style="margin: 40px;")
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filtering_process = Div(
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Section(
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@@ -139,7 +489,7 @@ filtering_process = Div(
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Ol(
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Li("This data was part of paper domain which are combined together and minhash was generated and deduped together with all the datasets after doing local dedup."),
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),
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-
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),
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Section(
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H3("S2ORC"),
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@@ -174,7 +524,7 @@ filtering_process = Div(
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Ol(
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Li("This data was part of paper domain which are combined together and minhash was generated and deduped together with all the datasets after doing local dedup"),
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),
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-
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),
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Section(
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H3("PubMed"),
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@@ -203,7 +553,7 @@ filtering_process = Div(
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Ol(
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Li("This data was part of paper domain which are combined together and minhash was generated and deduped together with all the datasets after doing local dedup."),
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),
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-
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),
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Section(
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H3("Phil Papers"),
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@@ -226,7 +576,7 @@ filtering_process = Div(
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Ol(
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Li("This data was part of paper domain which are combined together and minhash was generated and deduped together with all the datasets after doing local dedup."),
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),
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-
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),
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Section(
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H3("Europarl"),
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Ol(
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Li("After local dedup, remaining europarl was deduped again with all the datasets combined"),
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),
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-
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),
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Section(
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H3("HackerNews"),
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@@ -273,7 +623,7 @@ filtering_process = Div(
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Ol(
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Li("After local dedup, remaining data was deduped again with all the datasets combined"),
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),
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-
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),
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Section(
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H3("USPTO"),
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@@ -297,7 +647,7 @@ filtering_process = Div(
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Ol(
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Li("After local dedup, remaining data was deduped again with all the datasets combined"),
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),
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-
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),
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Section(
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H3("FreeLaw"),
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@@ -325,7 +675,7 @@ filtering_process = Div(
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Ol(
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Li("After local dedup, remaining data was deduped again with all the datasets combined"),
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),
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-
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),
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Section(
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H3("StackExchange"),
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@@ -358,7 +708,7 @@ filtering_process = Div(
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Ol(
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Li("After local dedup, remaining data was deduped again with all the datasets combined"),
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),
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-
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),
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Section(
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H3("Ubuntu IRC"),
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@@ -382,7 +732,7 @@ filtering_process = Div(
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Ol(
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Li("After local dedup, remaining data was deduped again with all the datasets combined"),
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),
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-
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),
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Section(
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H3("DM Maths"),
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@@ -403,7 +753,7 @@ filtering_process = Div(
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Ol(
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Li("None"),
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),
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-
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),
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Section(
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H3("PG19"),
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@@ -425,7 +775,7 @@ filtering_process = Div(
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Ol(
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Li("After local dedup, remaining data was deduped again with all the datasets combined"),
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),
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-
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),
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)
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"Percent Removed After Unigram Probability Filter": [
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"0.00%",
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],
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+
"Percent Removed After Local Dedup": [
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"",
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],
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"Total Percentage Remaining": [
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table_html_wikipedia = wikipedia_filter.to_html(index=False, border=0)
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table_div_wikipedia = Div(NotStr(table_html_wikipedia), style="margin: 40px;")
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+
freelaw_filter = pd.DataFrame(
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{
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"Dataset": [
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"Wikipedia",
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+
],
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+
"Lines Downloaded": [
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"61614907",
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+
],
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"Percent Removed After Language Filter": [
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"0.00%",
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+
],
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+
"Percent Removed After Min Word Count Filter": [
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"1.86%",
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+
],
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+
"Percent Removed After Unigram Probability Filter": [
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+
"0.00%",
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+
],
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+
"Percent Removed After Local Dedup": [
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+
"",
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+
],
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+
"Total Percentage Remaining": [
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+
"98.14%",
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+
],
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}
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+
)
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+
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+
table_html_freelaw = freelaw_filter.to_html(index=False, border=0)
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+
table_div_freelaw = Div(NotStr(table_html_freelaw), style="margin: 40px;")
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+
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+
dmm_filter = pd.DataFrame(
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{
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"Dataset": [
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+
"Wikipedia",
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+
],
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+
"Lines Downloaded": [
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+
"61614907",
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+
],
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+
"Percent Removed After Language Filter": [
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+
"0.00%",
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],
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+
"Percent Removed After Min Word Count Filter": [
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+
"1.86%",
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+
],
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+
"Percent Removed After Unigram Probability Filter": [
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+
"0.00%",
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+
],
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+
"Percent Removed After Local Dedup": [
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+
"",
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+
],
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+
"Total Percentage Remaining": [
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+
"98.14%",
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+
],
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}
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+
)
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+
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table_html_dmm = dmm_filter.to_html(index=False, border=0)
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+
table_div_dmm = Div(NotStr(table_html_dmm), style="margin: 40px;")
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+
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+
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+
uspto_filter = pd.DataFrame(
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{
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"Dataset": [
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+
"Wikipedia",
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+
],
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+
"Lines Downloaded": [
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+
"61614907",
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+
],
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+
"Percent Removed After Language Filter": [
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+
"0.00%",
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+
],
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+
"Percent Removed After Min Word Count Filter": [
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+
"1.86%",
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+
],
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+
"Percent Removed After Unigram Probability Filter": [
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+
"0.00%",
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+
],
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+
"Percent Removed After Local Dedup": [
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+
"",
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+
],
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+
"Total Percentage Remaining": [
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+
"98.14%",
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+
],
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+
}
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+
)
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+
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+
table_html_uspto = uspto_filter.to_html(index=False, border=0)
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+
table_div_uspto = Div(NotStr(table_html_uspto), style="margin: 40px;")
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+
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+
pg19_filter = pd.DataFrame(
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+
{
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| 179 |
+
"Dataset": [
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| 180 |
+
"Wikipedia",
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+
],
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| 182 |
+
"Lines Downloaded": [
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+
"61614907",
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+
],
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| 185 |
+
"Percent Removed After Language Filter": [
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| 186 |
+
"0.00%",
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+
],
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| 188 |
+
"Percent Removed After Min Word Count Filter": [
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| 189 |
+
"1.86%",
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| 190 |
+
],
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| 191 |
+
"Percent Removed After Unigram Probability Filter": [
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| 192 |
+
"0.00%",
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| 193 |
+
],
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| 194 |
+
"Percent Removed After Local Dedup": [
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| 195 |
+
"",
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| 196 |
+
],
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| 197 |
+
"Total Percentage Remaining": [
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| 198 |
+
"98.14%",
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+
],
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| 200 |
+
}
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+
)
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| 202 |
+
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+
table_html_pg19 = pg19_filter.to_html(index=False, border=0)
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+
table_div_pg19 = Div(NotStr(table_html_pg19), style="margin: 40px;")
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+
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+
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+
hn_filter = pd.DataFrame(
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+
{
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| 209 |
+
"Dataset": [
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"Wikipedia",
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],
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+
"Lines Downloaded": [
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+
"61614907",
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+
],
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| 215 |
+
"Percent Removed After Language Filter": [
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+
"0.00%",
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+
],
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+
"Percent Removed After Min Word Count Filter": [
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+
"1.86%",
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+
],
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| 221 |
+
"Percent Removed After Unigram Probability Filter": [
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+
"0.00%",
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+
],
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| 224 |
+
"Percent Removed After Local Dedup": [
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| 225 |
+
"",
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| 226 |
+
],
|
| 227 |
+
"Total Percentage Remaining": [
|
| 228 |
+
"98.14%",
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+
],
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| 230 |
+
}
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+
)
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+
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+
table_html_hn = hn_filter.to_html(index=False, border=0)
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| 234 |
+
table_div_hn = Div(NotStr(table_html_hn), style="margin: 40px;")
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+
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| 236 |
+
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| 237 |
+
uirc_filter = pd.DataFrame(
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| 238 |
+
{
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| 239 |
+
"Dataset": [
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| 240 |
+
"Wikipedia",
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+
],
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| 242 |
+
"Lines Downloaded": [
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| 243 |
+
"61614907",
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| 244 |
+
],
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| 245 |
+
"Percent Removed After Language Filter": [
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| 246 |
+
"0.00%",
|
| 247 |
+
],
|
| 248 |
+
"Percent Removed After Min Word Count Filter": [
|
| 249 |
+
"1.86%",
|
| 250 |
+
],
|
| 251 |
+
"Percent Removed After Unigram Probability Filter": [
|
| 252 |
+
"0.00%",
|
| 253 |
+
],
|
| 254 |
+
"Percent Removed After Local Dedup": [
|
| 255 |
+
"",
|
| 256 |
+
],
|
| 257 |
+
"Total Percentage Remaining": [
|
| 258 |
+
"98.14%",
|
| 259 |
+
],
|
| 260 |
+
}
|
| 261 |
+
)
|
| 262 |
+
|
| 263 |
+
table_html_uirc = uirc_filter.to_html(index=False, border=0)
|
| 264 |
+
table_div_uirc = Div(NotStr(table_html_uirc), style="margin: 40px;")
|
| 265 |
+
|
| 266 |
+
up_filter = pd.DataFrame(
|
| 267 |
+
{
|
| 268 |
+
"Dataset": [
|
| 269 |
+
"Wikipedia",
|
| 270 |
+
],
|
| 271 |
+
"Lines Downloaded": [
|
| 272 |
+
"61614907",
|
| 273 |
+
],
|
| 274 |
+
"Percent Removed After Language Filter": [
|
| 275 |
+
"0.00%",
|
| 276 |
+
],
|
| 277 |
+
"Percent Removed After Min Word Count Filter": [
|
| 278 |
+
"1.86%",
|
| 279 |
+
],
|
| 280 |
+
"Percent Removed After Unigram Probability Filter": [
|
| 281 |
+
"0.00%",
|
| 282 |
+
],
|
| 283 |
+
"Percent Removed After Local Dedup": [
|
| 284 |
+
"",
|
| 285 |
+
],
|
| 286 |
+
"Total Percentage Remaining": [
|
| 287 |
+
"98.14%",
|
| 288 |
+
],
|
| 289 |
+
}
|
| 290 |
+
)
|
| 291 |
+
|
| 292 |
+
table_html_up = up_filter.to_html(index=False, border=0)
|
| 293 |
+
table_div_up = Div(NotStr(table_html_up), style="margin: 40px;")
|
| 294 |
+
|
| 295 |
+
se_filter = pd.DataFrame(
|
| 296 |
+
{
|
| 297 |
+
"Dataset": [
|
| 298 |
+
"Wikipedia",
|
| 299 |
+
],
|
| 300 |
+
"Lines Downloaded": [
|
| 301 |
+
"61614907",
|
| 302 |
+
],
|
| 303 |
+
"Percent Removed After Language Filter": [
|
| 304 |
+
"0.00%",
|
| 305 |
+
],
|
| 306 |
+
"Percent Removed After Min Word Count Filter": [
|
| 307 |
+
"1.86%",
|
| 308 |
+
],
|
| 309 |
+
"Percent Removed After Unigram Probability Filter": [
|
| 310 |
+
"0.00%",
|
| 311 |
+
],
|
| 312 |
+
"Percent Removed After Local Dedup": [
|
| 313 |
+
"",
|
| 314 |
+
],
|
| 315 |
+
"Total Percentage Remaining": [
|
| 316 |
+
"98.14%",
|
| 317 |
+
],
|
| 318 |
+
}
|
| 319 |
+
)
|
| 320 |
+
|
| 321 |
+
table_html_se = se_filter.to_html(index=False, border=0)
|
| 322 |
+
table_div_se = Div(NotStr(table_html_se), style="margin: 40px;")
|
| 323 |
+
|
| 324 |
+
arx_filter = pd.DataFrame(
|
| 325 |
+
{
|
| 326 |
+
"Dataset": [
|
| 327 |
+
"Wikipedia",
|
| 328 |
+
],
|
| 329 |
+
"Lines Downloaded": [
|
| 330 |
+
"61614907",
|
| 331 |
+
],
|
| 332 |
+
"Percent Removed After Language Filter": [
|
| 333 |
+
"0.00%",
|
| 334 |
+
],
|
| 335 |
+
"Percent Removed After Min Word Count Filter": [
|
| 336 |
+
"1.86%",
|
| 337 |
+
],
|
| 338 |
+
"Percent Removed After Unigram Probability Filter": [
|
| 339 |
+
"0.00%",
|
| 340 |
+
],
|
| 341 |
+
"Percent Removed After Local Dedup": [
|
| 342 |
+
"",
|
| 343 |
+
],
|
| 344 |
+
"Total Percentage Remaining": [
|
| 345 |
+
"98.14%",
|
| 346 |
+
],
|
| 347 |
+
}
|
| 348 |
+
)
|
| 349 |
+
|
| 350 |
+
table_html_arx = arx_filter.to_html(index=False, border=0)
|
| 351 |
+
table_div_arx = Div(NotStr(table_html_arx), style="margin: 40px;")
|
| 352 |
+
|
| 353 |
+
s2o_filter = pd.DataFrame(
|
| 354 |
+
{
|
| 355 |
+
"Dataset": [
|
| 356 |
+
"Wikipedia",
|
| 357 |
+
],
|
| 358 |
+
"Lines Downloaded": [
|
| 359 |
+
"61614907",
|
| 360 |
+
],
|
| 361 |
+
"Percent Removed After Language Filter": [
|
| 362 |
+
"0.00%",
|
| 363 |
+
],
|
| 364 |
+
"Percent Removed After Min Word Count Filter": [
|
| 365 |
+
"1.86%",
|
| 366 |
+
],
|
| 367 |
+
"Percent Removed After Unigram Probability Filter": [
|
| 368 |
+
"0.00%",
|
| 369 |
+
],
|
| 370 |
+
"Percent Removed After Local Dedup": [
|
| 371 |
+
"",
|
| 372 |
+
],
|
| 373 |
+
"Total Percentage Remaining": [
|
| 374 |
+
"98.14%",
|
| 375 |
+
],
|
| 376 |
+
}
|
| 377 |
+
)
|
| 378 |
+
|
| 379 |
+
table_html_s2o = s2o_filter.to_html(index=False, border=0)
|
| 380 |
+
table_div_s2o = Div(NotStr(table_html_s2o), style="margin: 40px;")
|
| 381 |
+
|
| 382 |
+
med_filter = pd.DataFrame(
|
| 383 |
+
{
|
| 384 |
+
"Dataset": [
|
| 385 |
+
"Wikipedia",
|
| 386 |
+
],
|
| 387 |
+
"Lines Downloaded": [
|
| 388 |
+
"61614907",
|
| 389 |
+
],
|
| 390 |
+
"Percent Removed After Language Filter": [
|
| 391 |
+
"0.00%",
|
| 392 |
+
],
|
| 393 |
+
"Percent Removed After Min Word Count Filter": [
|
| 394 |
+
"1.86%",
|
| 395 |
+
],
|
| 396 |
+
"Percent Removed After Unigram Probability Filter": [
|
| 397 |
+
"0.00%",
|
| 398 |
+
],
|
| 399 |
+
"Percent Removed After Local Dedup": [
|
| 400 |
+
"",
|
| 401 |
+
],
|
| 402 |
+
"Total Percentage Remaining": [
|
| 403 |
+
"98.14%",
|
| 404 |
+
],
|
| 405 |
+
}
|
| 406 |
+
)
|
| 407 |
+
|
| 408 |
+
table_html_med = med_filter.to_html(index=False, border=0)
|
| 409 |
+
table_div_med = Div(NotStr(table_html_med), style="margin: 40px;")
|
| 410 |
+
|
| 411 |
+
phil_filter = pd.DataFrame(
|
| 412 |
+
{
|
| 413 |
+
"Dataset": [
|
| 414 |
+
"Wikipedia",
|
| 415 |
+
],
|
| 416 |
+
"Lines Downloaded": [
|
| 417 |
+
"61614907",
|
| 418 |
+
],
|
| 419 |
+
"Percent Removed After Language Filter": [
|
| 420 |
+
"0.00%",
|
| 421 |
+
],
|
| 422 |
+
"Percent Removed After Min Word Count Filter": [
|
| 423 |
+
"1.86%",
|
| 424 |
+
],
|
| 425 |
+
"Percent Removed After Unigram Probability Filter": [
|
| 426 |
+
"0.00%",
|
| 427 |
+
],
|
| 428 |
+
"Percent Removed After Local Dedup": [
|
| 429 |
+
"",
|
| 430 |
+
],
|
| 431 |
+
"Total Percentage Remaining": [
|
| 432 |
+
"98.14%",
|
| 433 |
+
],
|
| 434 |
+
}
|
| 435 |
+
)
|
| 436 |
+
|
| 437 |
+
table_html_phil = phil_filter.to_html(index=False, border=0)
|
| 438 |
+
table_div_phil = Div(NotStr(table_html_phil), style="margin: 40px;")
|
| 439 |
|
| 440 |
filtering_process = Div(
|
| 441 |
Section(
|
|
|
|
| 489 |
Ol(
|
| 490 |
Li("This data was part of paper domain which are combined together and minhash was generated and deduped together with all the datasets after doing local dedup."),
|
| 491 |
),
|
| 492 |
+
table_div_arx,
|
| 493 |
),
|
| 494 |
Section(
|
| 495 |
H3("S2ORC"),
|
|
|
|
| 524 |
Ol(
|
| 525 |
Li("This data was part of paper domain which are combined together and minhash was generated and deduped together with all the datasets after doing local dedup"),
|
| 526 |
),
|
| 527 |
+
table_div_s2o,
|
| 528 |
),
|
| 529 |
Section(
|
| 530 |
H3("PubMed"),
|
|
|
|
| 553 |
Ol(
|
| 554 |
Li("This data was part of paper domain which are combined together and minhash was generated and deduped together with all the datasets after doing local dedup."),
|
| 555 |
),
|
| 556 |
+
table_div_med,
|
| 557 |
),
|
| 558 |
Section(
|
| 559 |
H3("Phil Papers"),
|
|
|
|
| 576 |
Ol(
|
| 577 |
Li("This data was part of paper domain which are combined together and minhash was generated and deduped together with all the datasets after doing local dedup."),
|
| 578 |
),
|
| 579 |
+
table_div_phil,
|
| 580 |
),
|
| 581 |
Section(
|
| 582 |
H3("Europarl"),
|
|
|
|
| 598 |
Ol(
|
| 599 |
Li("After local dedup, remaining europarl was deduped again with all the datasets combined"),
|
| 600 |
),
|
| 601 |
+
table_div_up,
|
| 602 |
),
|
| 603 |
Section(
|
| 604 |
H3("HackerNews"),
|
|
|
|
| 623 |
Ol(
|
| 624 |
Li("After local dedup, remaining data was deduped again with all the datasets combined"),
|
| 625 |
),
|
| 626 |
+
table_div_hn,
|
| 627 |
),
|
| 628 |
Section(
|
| 629 |
H3("USPTO"),
|
|
|
|
| 647 |
Ol(
|
| 648 |
Li("After local dedup, remaining data was deduped again with all the datasets combined"),
|
| 649 |
),
|
| 650 |
+
table_div_uspto,
|
| 651 |
),
|
| 652 |
Section(
|
| 653 |
H3("FreeLaw"),
|
|
|
|
| 675 |
Ol(
|
| 676 |
Li("After local dedup, remaining data was deduped again with all the datasets combined"),
|
| 677 |
),
|
| 678 |
+
table_div_freelaw,
|
| 679 |
),
|
| 680 |
Section(
|
| 681 |
H3("StackExchange"),
|
|
|
|
| 708 |
Ol(
|
| 709 |
Li("After local dedup, remaining data was deduped again with all the datasets combined"),
|
| 710 |
),
|
| 711 |
+
table_div_se,
|
| 712 |
),
|
| 713 |
Section(
|
| 714 |
H3("Ubuntu IRC"),
|
|
|
|
| 732 |
Ol(
|
| 733 |
Li("After local dedup, remaining data was deduped again with all the datasets combined"),
|
| 734 |
),
|
| 735 |
+
table_div_uirc,
|
| 736 |
),
|
| 737 |
Section(
|
| 738 |
H3("DM Maths"),
|
|
|
|
| 753 |
Ol(
|
| 754 |
Li("None"),
|
| 755 |
),
|
| 756 |
+
table_div_dmm,
|
| 757 |
),
|
| 758 |
Section(
|
| 759 |
H3("PG19"),
|
|
|
|
| 775 |
Ol(
|
| 776 |
Li("After local dedup, remaining data was deduped again with all the datasets combined"),
|
| 777 |
),
|
| 778 |
+
table_div_pg19,
|
| 779 |
),
|
| 780 |
)
|
| 781 |
|