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llm-datasets

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A framework to analyze how AGI/ASI might emerge from decentralized, adaptive systems, rather than as the fruit of a single model deployment. It also aims to present orientation as a dynamic and self-evolving Magna Carta, helping to guide the emergence of such phenomena.

  • Updated Aug 6, 2025

Synthetically Generating Intent-Aware Information-Seeking Dialogues! Useful for various tasks such as training/evaluating User Intent Predictors with the possibility to training/evaluating on real human dialogues. The backbone LLM of SOLID is Zephyr-7b-beta.

  • Updated Aug 18, 2024
  • Python

RepoCapsule is a Python toolkit for turning GitHub, local, and other text/code sources into clean JSONL corpora for LLM pre-training, fine-tuning, or RAG. It provides structure-aware chunking, robust Unicode decoding, pluggable quality/safety screening, and optional dataset card + deduplication support.

  • Updated Dec 7, 2025
  • Python

Stratified LLM Subsets delivers diverse training data at 100K-1M scales across pre-training (FineWeb-Edu, Proof-Pile-2), instruction-following (Tulu-3, Orca AgentInstruct), and reasoning distillation (Llama-Nemotron). Embedding-based k-means clustering ensures maximum diversity across 5 high-quality open datasets.

  • Updated Oct 4, 2025
  • HTML

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