add minhash to table

README.md

@@ -78,7 +78,8 @@ A full set of scripts to recreate the dataset, including the quality signals, ca
 found [here](https://github.com/togethercomputer/RedPajama-Data).
 
 ### Applying Filtering Rules
-You can use the quality signals to filter the raw RedPajama-V2 dataset for a given set of rules. For example, consider 
+
+You can use the quality signals to filter the raw RedPajama-V2 dataset for a given set of rules. For example, consider
 the following set of rules used in Gopher:
 
 ```python
@@ -98,7 +99,7 @@ def gopher_rules_pass(sample) -> bool:
 
     # rule 2: symbol to word ratio below 0.1
     symbol_word_ratio = signals["rps_doc_symbol_to_word_ratio"][0][2]
-    if  symbol_word_ratio > 0.1:
+    if symbol_word_ratio > 0.1:
         return False
 
     # rule 3: 90% of lines need to start without a bullet point
@@ -114,8 +115,7 @@ def gopher_rules_pass(sample) -> bool:
         return False
 
     # rule 5: ...
-    
-        
+
     return True
 ```
 
@@ -123,21 +123,21 @@ Filtering the RedPajama-V2 dataset with this set of rules is then as easy as:
 
 ```python
 ds_iterator = load_dataset(
-    "togethercomputer/RedPajama-Data-V2", 
-    snapshots=["2023-14"], 
-    languages=["en"], 
-    name="default", 
+    "togethercomputer/RedPajama-Data-V2",
+    snapshots=["2023-14"],
+    languages=["en"],
+    name="default",
     streaming=True
 )
 
 filtered_dataset = []
 
 for sample in ds_iterator["train"]:
-  
-  if not gopher_rules_pass(sample):
-    continue
-  
-  filtered_dataset.append(sample)
+
+    if not gopher_rules_pass(sample):
+        continue
+
+    filtered_dataset.append(sample)
 ```
 
 ### Dataset Summary
@@ -191,6 +191,10 @@ RedPajama-V2 is an open dataset for training large laguage models and includes o
 | rps_doc_frac_chars_top_4gram                   | The fraction of characters in the top word 4gram.                                                                                                                                                                                                                                                                                                                                                                    | Repetitiveness   | [RefinedWeb](https://arxiv.org/abs/2306.01116), [Gopher](https://arxiv.org/abs/2112.11446)                                    |
 | rps_doc_ldnoobw_words                          | The number of sequences of words that are contained in the List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words blocklist. The blocklist is obtained from the [LDNOOBW](https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words) repo.                                                                                                                                                     | toxicity         | [C4](https://arxiv.org/abs/1910.10683)                                                                                        |
 | rps_doc_ut1_blacklist                          | A categorical id corresponding to the list of categories of the domain of the document. Categories are obtained from the UT1 blacklist. The list is obtained from [UT-Capitole](https://dsi.ut-capitole.fr/blacklists/).                                                                                                                                                                                             | toxicictiy       | [RefinedWeb](https://arxiv.org/abs/2306.01116)                                                                                |
+| minhash_signature_0.7                          | Banded minhash signature of the document, for fuzzy deduplication at Jaccard similarity 0.7                                                                                                                                                                                                                                                                                                                          | Deduplication    |
+| minhash_signature_0.8                          | Banded minhash signature of the document, for fuzzy deduplication at Jaccard similarity 0.8                                                                                                                                                                                                                                                                                                                          | Deduplication    |
+| minhash_signature_0.9                          | Banded minhash signature of the document, for fuzzy deduplication at Jaccard similarity 0.9                                                                                                                                                                                                                                                                                                                          | Deduplication    |
+| minhash_signature_1.0                          | Banded minhash signature of the document, for fuzzy deduplication at Jaccard similarity 1.0                                                                                                                                                                                                                                                                                                                          | Deduplication    |
 
 #### Document and Token Counts for the Annotated and deduplicated `head_middle` part of the dataset