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+ ---
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+ license: mit
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+ annotations_creators:
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+ - no-annotation
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+ language:
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+ - en
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 10M<n<100M
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - text-generation
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+ - text-scoring
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+ task_ids:
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+ - language-modeling
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+ - sentiment-analysis
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+ - toxicity-detection
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+ pretty_name: Discord Messages 2026
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+ tags:
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+ - discord
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+ - social-media
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+ - chat
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+ - conversation
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+ - nlp
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+ - text-generation
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+ ---
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+
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+ # Discord Messages Dataset
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+
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+ ## Description
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+
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+ This dataset contains **6.2 million anonymized messages** extracted from public Discord servers. All personal identifying information (user IDs, server IDs, channel IDs, timestamps) has been removed. Only the raw message text remains.
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+
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+ The data is formatted as plain text with **one message per line**, making it ideal for:
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+ - Language model pre-training
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+ - Fine-tuning chatbots
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+ - Sentiment analysis
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+ - Toxicity detection
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+ - Slang and language evolution research
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+ - Conversational AI training
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+
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+ ## Dataset Statistics
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+
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+ | Metric | Value |
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+ |--------|-------|
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+ | **Total messages** | 6,200,934 |
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+ | **File size** | 487 MB |
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+ | **Format** | Plain text (UTF-8) |
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+ | **Lines** | 6,200,934 |
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+ | **Language** | English (primarily) |
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+ | **Average message length** | ~78 characters |
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+
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+ ## Data Format
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+
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+ Each line contains a single message:
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+ hey guys whats up
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+ anyone wanna play?
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+ looking for group
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+ i'm so bored rn
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+ can someone help me with this
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+
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+
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+ ## Usage Examples
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+
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+ ### Python
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+
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+ ```python
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+ # Load and iterate through messages
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+ with open('messages_only.txt', 'r', encoding='utf-8') as f:
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+ for line in f:
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+ message = line.strip()
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+ # Process message
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+ print(message)```
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+