Remove more blanks and ToS breaking content

CHANGELOG → CHANGEGLOG

@@ -2,4 +2,6 @@ v.01 - Inital upload
 v.02 - Further deduping
 v.03 - ToS filtered. Added filters script repo
 v.04 - Fixed end tags and emoticons having missing leading spaces
-v.05 - Added dataset pipeline
+v.05 - Added dataset pipeline
+v.06 - Removed entries with blank messages
+v.07 - Remove addition blanks and filtered for more ToS

README.md

@@ -29,7 +29,7 @@ size_categories:
 
 > **Discord-Dialogues** is a large-scale dataset of anonymized Discord conversations from late spring to early fall 2025 for training and evaluating realistic conversational AI models in a ChatML-friendly format.
 
-  This dataset contains 7.5 million exchanges spread out over 17 million turns, with more than 145 million words. 
+This dataset contains 7.3 million exchanges spread out over 16 million turns, with more than 139 million words.
 
 ---
 
@@ -59,9 +59,10 @@ size_categories:
 -   Training relevance/reward models
 -   Dialogue generation research
 
-Use case examples:  
-- [mookiezi/Discord-Micae-8B-Preview](https://huggingface.co/mookiezi/Discord-Micae-8B-Preview) — experimental larger model  
-- [mookiezi/Discord-Micae-Hermes-3-3B](https://huggingface.co/mookiezi/Discord-Micae-Hermes-3-3B) — stable smaller model
+Use case examples:
+
+-   [mookiezi/Discord-Micae-8B-Preview](https://huggingface.co/mookiezi/Discord-Micae-8B-Preview) — experimental larger model
+-   [mookiezi/Discord-Micae-Hermes-3-3B](https://huggingface.co/mookiezi/Discord-Micae-Hermes-3-3B) — stable smaller model
 
 ---
 
@@ -70,22 +71,22 @@ Use case examples:
 This dataset was constructed with a custom multi-stage filtering toolkit:
 
 1. **SQL filters** (`filter.sql`)  
-  Postgres regex/text filters for PII, bot/command patterns, links, embeds, and automation noise.
+   Postgres regex/text filters for PII, bot/command patterns, links, embeds, and automation noise.
 
 2. **Smart cleaner** (`smartclean.py`)  
-  Multi-stage process: normalize text, slang replacement, resample by length, and enforce structural validation.
-  Filters out structural noise such as code blocks, trading posts, and LFG.
+   Multi-stage process: normalize text, slang replacement, resample by length, and enforce structural validation.
+   Filters out structural noise such as code blocks, trading posts, and LFG.
 
 3. **Dedupe** (`dedupe.py`)
-  Deduplicates conversations by hashing message chains
-  Keeps only unique rows preferring the longest final assistant message when duplicates occur.
+   Deduplicates conversations by hashing message chains
+   Keeps only unique rows preferring the longest final assistant message when duplicates occur.
 
 4. **Fix End** (`fixend.py`)
-  Strips any prefix of spaces, commas, or non-emoticon colons before `<|im_end|>` to the plain token.
+   Strips any prefix of spaces, commas, or non-emoticon colons before `<|im_end|>` to the plain token.
 
 5. **ToS risk filter** (`tos.py`)
-  Drops or redacts unsafe categories (sexual violence, CSA, slurs, harassment, doxxing, self-harm, extremism) and PII.
-  Uses fuzzy/leet/diacritic-aware regex.
+   Drops or redacts unsafe categories (sexual violence, CSA, slurs, harassment, doxxing, self-harm, extremism) and PII.
+   Uses fuzzy/leet/diacritic-aware regex.
 
 The full filtering scripts are open source at the [filters GitHub repository](https://github.com/mookiezi/filters).
 
@@ -109,80 +110,78 @@ The full end-to-end pipeline is documented in the [dataset-pipeline GitHub repos
 
 <div>
 
-| Metric                   |           Value  |
-| ------------------------ | --------------:  |
-| Samples (count)          |        7,546,294 |
-| Min length (tokens)      |                7 |
-| Max length (tokens)      |            5,979 |
-| Mean length (tokens)     |            33.02 |
-| Median length (tokens)   |               29 |
-| Std dev (tokens)         |            17.39 |
-| Skew                     |            26.46 |
-| Kurtosis                 |         7,487.55 |
-| Total tokens             |      249,193,745 |
-| Total characters         |    1,291,480,299 |
-| Total words              |      145,887,976 |
-| Avg chars per sample     |           171.14 |
-| Avg words per sample     |            19.33 |
-| Avg chars per word       |             8.85 |
-| Tokens per char          |             0.19 |
-| Total assistant blocks   |        9,341,891 |
+| Metric                 |         Value |
+| ---------------------- | ------------: |
+| Samples (count)        |     7,303,464 |
+| Total turns            |    16,881,010 |
+| Total assistant turns  |     9,016,287 |
+| Min length (tokens)    |            10 |
+| Max length (tokens)    |         2,542 |
+| Mean length (tokens)   |         32.79 |
+| Median length (tokens) |            28 |
+| Std dev (tokens)       |         16.56 |
+| Skew                   |          6.04 |
+| Kurtosis               |        326.54 |
+| Total tokens           |   239,458,213 |
+| Total characters       | 1,242,238,794 |
+| Total words            |   139,922,950 |
+| Avg chars per sample   |        170.09 |
+| Avg words per sample   |         19.16 |
+| Avg chars per word     |          8.88 |
+| Tokens per char        |          0.19 |
 
 </div>
 
 <div>
 
-
-| Tokens    |     Count  |
-| --------- | --------:  |
-| 0–8       |         1  |
-| 8–16      |    110,310 |
-| 16–32     |  4,382,094 |
-| 32–64     |  2,674,780 |
-| 64–128    |    360,401 |
-| 128–256   |     18,083 |
-| 256–384   |        417 |
-| 384–512   |         75 |
-| 512–768   |         78 |
-| 768–1024  |         30 |
-| 1024–2048 |         18 |
-| 2048–4096 |          3 |
+| Tokens    |     Count |
+| --------- | --------: |
+| 8–16      |   107,264 |
+| 16–32     | 4,278,713 |
+| 32–64     | 2,566,176 |
+| 64–128    |   334,829 |
+| 128–256   |    15,920 |
+| 256–384   |       363 |
+| 384–512   |        71 |
+| 512–768   |        78 |
+| 768–1024  |        30 |
+| 1024–2048 |        17 |
+| 2048–4096 |         3 |
 
 </div>
 
 <div>
 
-
-| Turns |   Count    |
-| ----- | --------:  |
-| 2     |  5,969,540 |
-| 3     |  1,080,526 |
-| 4     |    319,794 |
-| 5     |    102,553 |
-| 6     |     41,246 |
-| 7     |     16,904 |
-| 8     |      7,715 |
-| 9     |      3,691 |
-| 10    |      1,867 |
-| 11    |      1,007 |
-| 12    |        575 |
-| 13    |        334 |
-| 14    |        189 |
-| 15    |        129 |
-| 16    |         67 |
-| 17    |         62 |
-| 18    |         32 |
-| 19    |         21 |
-| 20    |          8 |
-| 21    |         11 |
-| 22    |         11 |
-| 23    |          2 |
-| 24    |          1 |
-| 25    |          3 |
-| 27    |          2 |
-| 29    |          1 |
-| 32    |          1 |
-| 33    |          2 |
+| Turns |     Count |
+| ----- | --------: |
+| 2     | 5,795,019 |
+| 3     | 1,038,500 |
+| 4     |   304,442 |
+| 5     |    96,758 |
+| 6     |    38,620 |
+| 7     |    15,714 |
+| 8     |     7,108 |
+| 9     |     3,391 |
+| 10    |     1,709 |
+| 11    |       909 |
+| 12    |       526 |
+| 13    |       291 |
+| 14    |       163 |
+| 15    |       113 |
+| 16    |        58 |
+| 17    |        57 |
+| 18    |        28 |
+| 19    |        20 |
+| 20    |         7 |
+| 21    |        10 |
+| 22    |        10 |
+| 23    |         2 |
+| 24    |         1 |
+| 25    |         2 |
+| 27    |         2 |
+| 29    |         1 |
+| 32    |         1 |
+| 33    |         2 |
 
 </div>
 

train.parquet → data/train.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fe52210778f5d71724664d9c365a71599913f93c30cc60df8e674dd3c45c08ca
-size 362018517
+oid sha256:241e350e7f651085c5c2cb4d5274f7cb671b84b3d5fba091101823678da454ec
+size 346784147

dataset_infos.json

@@ -1,29 +1,29 @@
 {
-  "default": {
-    "description": "Discord-Dialogues is a large-scale dataset of anonymized Discord conversations formatted for ChatML. It includes mixed single- and multi-turn exchanges between two human participants, cleaned of bots, links, embeds, commands, ToS breaking content, and duplicate messages—primarily in English, suitable for fine-tuning conversational AI models.",
-    "citation": "@misc{discord-dialogues-2025,\n  title = {Discord-Dialogues},\n  author = {mookiezi},\n  year = {2025},\n  url = {https://huggingface.co/datasets/mookiezi/Discord-Dialogues}\n}",
-    "homepage": "https://huggingface.co/datasets/mookiezi/Discord-Dialogues",
-    "license": "Apache License 2.0",
-    "features": {
-      "text": { "dtype": "string", "_type": "Value" },
-      "tokens": { "dtype": "int64", "_type": "Value" },
-      "turns": { "dtype": "int64", "_type": "Value" },
-      "characters": { "dtype": "int64", "_type": "Value" },
-      "words": { "dtype": "int64", "_type": "Value" }
-    },
-    "splits": {
-      "train": {
-        "name": "train",
-        "num_bytes": 362022690,
-        "num_examples": 7546294,
-        "dataset_name": "default"
-      }
-    },
-    "download_size": 362022690,
-    "dataset_size": 362022690,
-    "size_in_bytes": 362022690,
-    "data_files": {
-      "train": [{ "filename": "train.parquet" }]
-    }
-  }
-}
+	"default": {
+		"description": "Discord-Dialogues is a large-scale dataset of anonymized Discord conversations formatted for ChatML. It includes mixed single- and multi-turn exchanges between two human participants, cleaned of bots, links, embeds, commands, ToS breaking content, and duplicate messages—primarily in English, suitable for fine-tuning conversational AI models.",
+		"citation": "@misc{discord-dialogues-2025,\n  title = {Discord-Dialogues},\n  author = {mookiezi},\n  year = {2025},\n  url = {https://huggingface.co/datasets/mookiezi/Discord-Dialogues}\n}",
+		"homepage": "https://huggingface.co/datasets/mookiezi/Discord-Dialogues",
+		"license": "Apache License 2.0",
+		"features": {
+			"text": { "dtype": "string", "_type": "Value" },
+			"tokens": { "dtype": "int64", "_type": "Value" },
+			"turns": { "dtype": "int64", "_type": "Value" },
+			"characters": { "dtype": "int64", "_type": "Value" },
+			"words": { "dtype": "int64", "_type": "Value" }
+		},
+		"splits": {
+			"train": {
+				"name": "train",
+				"num_bytes": 346784147,
+				"num_examples": 7300966,
+				"dataset_name": "default"
+			}
+		},
+		"download_size": 346784147,
+		"dataset_size": 346784147,
+		"size_in_bytes": 346784147,
+		"data_files": {
+			"train": [{ "filename": "data/train.parquet" }]
+		}
+	}
+}

tokens.log

@@ -1,135 +0,0 @@
-Stats for text:
-  min: 7
-  max: 5979
-  mean: 33.02200325086725
-  median: 29.0
-  std: 17.390580671916503
-  skew: 26.456841814125784
-  kurt: 7487.549682758939
-  count: 7546294
-  sum: 249193745
-  99.9%: 152.0
-  1%: 15.0
-  2%: 16.0
-  3%: 16.0
-  4%: 17.0
-  5%: 17.0
-  6%: 18.0
-  7%: 18.0
-  8%: 18.0
-  9%: 19.0
-  10%: 19.0
-  11%: 19.0
-  12%: 19.0
-  13%: 20.0
-  14%: 20.0
-  15%: 20.0
-  16%: 20.0
-  17%: 21.0
-  18%: 21.0
-  19%: 21.0
-  20%: 21.0
-  21%: 22.0
-  22%: 22.0
-  23%: 22.0
-  24%: 22.0
-  25%: 22.0
-  26%: 23.0
-  27%: 23.0
-  28%: 23.0
-  29%: 23.0
-  30%: 24.0
-  31%: 24.0
-  32%: 24.0
-  33%: 24.0
-  34%: 24.0
-  35%: 25.0
-  36%: 25.0
-  37%: 25.0
-  38%: 25.0
-  39%: 26.0
-  40%: 26.0
-  41%: 26.0
-  42%: 26.0
-  43%: 27.0
-  44%: 27.0
-  45%: 27.0
-  46%: 27.0
-  47%: 28.0
-  48%: 28.0
-  49%: 28.0
-  50%: 29.0
-  51%: 29.0
-  52%: 29.0
-  53%: 29.0
-  54%: 30.0
-  55%: 30.0
-  56%: 30.0
-  57%: 31.0
-  58%: 31.0
-  59%: 31.0
-  60%: 32.0
-  61%: 32.0
-  62%: 32.0
-  63%: 33.0
-  64%: 33.0
-  65%: 34.0
-  66%: 34.0
-  67%: 34.0
-  68%: 35.0
-  69%: 35.0
-  70%: 36.0
-  71%: 36.0
-  72%: 37.0
-  73%: 37.0
-  74%: 38.0
-  75%: 38.0
-  76%: 39.0
-  77%: 39.0
-  78%: 40.0
-  79%: 41.0
-  80%: 42.0
-  81%: 42.0
-  82%: 43.0
-  83%: 44.0
-  84%: 45.0
-  85%: 46.0
-  86%: 47.0
-  87%: 48.0
-  88%: 49.0
-  89%: 51.0
-  90%: 52.0
-  91%: 54.0
-  92%: 56.0
-  93%: 58.0
-  94%: 60.0
-  95%: 64.0
-  96%: 68.0
-  97%: 73.0
-  98%: 80.0
-  99%: 95.0
-  100%: 5979.0
-  total_chars: 1291480299
-  total_words: 145887976
-  avg_chars: 171.14099967480726
-  avg_words: 19.332400248386826
-  avg_chars_per_word: 8.852547923483426
-  avg_chars_per_sample: 171.14099967480726
-  avg_words_per_sample: 19.332400248386826
-  tokens_per_char: 0.19295202969255673
-  bin_0-8: 1
-  bin_8-16: 110310
-  bin_16-32: 4382094
-  bin_32-64: 2674780
-  bin_64-128: 360401
-  bin_128-256: 18083
-  bin_256-384: 417
-  bin_384-512: 75
-  bin_512-768: 78
-  bin_768-1024: 30
-  bin_1024-2048: 18
-  bin_2048-4096: 3
-  assistant_blocks: 9341891
-
-Total tokens across all columns: 249193745
-Total assistant blocks: 9341891

tokenstats.txt

@@ -1,135 +0,0 @@
-Stats for text:
-  min: 8
-  max: 5979
-  mean: 33.024094354044
-  median: 29.0
-  std: 17.402215788976577
-  skew: 26.64223385581348
-  kurt: 7506.831274998159
-  count: 7543842
-  sum: 249128550
-  99.9%: 153.0
-  1%: 15.0
-  2%: 16.0
-  3%: 16.0
-  4%: 17.0
-  5%: 17.0
-  6%: 18.0
-  7%: 18.0
-  8%: 18.0
-  9%: 19.0
-  10%: 19.0
-  11%: 19.0
-  12%: 19.0
-  13%: 20.0
-  14%: 20.0
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-  16%: 20.0
-  17%: 21.0
-  18%: 21.0
-  19%: 21.0
-  20%: 21.0
-  21%: 22.0
-  22%: 22.0
-  23%: 22.0
-  24%: 22.0
-  25%: 22.0
-  26%: 23.0
-  27%: 23.0
-  28%: 23.0
-  29%: 23.0
-  30%: 24.0
-  31%: 24.0
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-  33%: 24.0
-  34%: 24.0
-  35%: 25.0
-  36%: 25.0
-  37%: 25.0
-  38%: 25.0
-  39%: 26.0
-  40%: 26.0
-  41%: 26.0
-  42%: 26.0
-  43%: 27.0
-  44%: 27.0
-  45%: 27.0
-  46%: 27.0
-  47%: 28.0
-  48%: 28.0
-  49%: 28.0
-  50%: 29.0
-  51%: 29.0
-  52%: 29.0
-  53%: 29.0
-  54%: 30.0
-  55%: 30.0
-  56%: 30.0
-  57%: 31.0
-  58%: 31.0
-  59%: 31.0
-  60%: 32.0
-  61%: 32.0
-  62%: 32.0
-  63%: 33.0
-  64%: 33.0
-  65%: 34.0
-  66%: 34.0
-  67%: 34.0
-  68%: 35.0
-  69%: 35.0
-  70%: 36.0
-  71%: 36.0
-  72%: 37.0
-  73%: 37.0
-  74%: 38.0
-  75%: 38.0
-  76%: 39.0
-  77%: 39.0
-  78%: 40.0
-  79%: 41.0
-  80%: 42.0
-  81%: 42.0
-  82%: 43.0
-  83%: 44.0
-  84%: 45.0
-  85%: 46.0
-  86%: 47.0
-  87%: 48.0
-  88%: 49.0
-  89%: 51.0
-  90%: 52.0
-  91%: 54.0
-  92%: 56.0
-  93%: 58.0
-  94%: 60.0
-  95%: 64.0
-  96%: 68.0
-  97%: 73.0
-  98%: 80.0
-  99%: 95.0
-  100%: 5979.0
-  total_chars: 1290998934
-  total_words: 145717457
-  avg_chars: 171.13281720375375
-  avg_words: 19.316080188317837
-  avg_chars_per_word: 8.85960378789756
-  avg_chars_per_sample: 171.13281720375375
-  avg_words_per_sample: 19.316080188317837
-  tokens_per_char: 0.19297347460087058
-  bin_0-8: 0
-  bin_8-16: 109538
-  bin_16-32: 4381031
-  bin_32-64: 2674243
-  bin_64-128: 360330
-  bin_128-256: 18072
-  bin_256-384: 418
-  bin_384-512: 78
-  bin_512-768: 77
-  bin_768-1024: 30
-  bin_1024-2048: 17
-  bin_2048-4096: 4
-  assistant_blocks: 9339690
-
-Total tokens across all columns: 249128550
-Total assistant blocks: 9339690