Post
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🚀 Introducing the xLLMs Dataset Collection
The xLLMs project is a growing suite of multilingual and multimodal dialogue datasets designed to train and evaluate advanced conversational LLMs. Each dataset focuses on a specific capability — from long-context reasoning and factual grounding to STEM explanations, math Q&A, and polite multilingual interaction.
🌍 Explore the full collection on Hugging Face:
👉 lamhieu/xllms-66cdfe34307bb2edc8c6df7d
💬 Highlight: xLLMs – Dialogue Pubs
A large-scale multilingual dataset built from document-guided synthetic dialogues (Wikipedia, WikiHow, and technical sources). It’s ideal for training models on long-context reasoning, multi-turn coherence, and tool-augmented dialogue across 9 languages.
👉 lamhieu/xllms_dialogue_pubs
🧠 Designed for:
- Long-context and reasoning models
- Multilingual assistants
- Tool-calling and structured response learning
All datasets are open for research and development use — free, transparent, and carefully curated to improve dialogue model quality.
The xLLMs project is a growing suite of multilingual and multimodal dialogue datasets designed to train and evaluate advanced conversational LLMs. Each dataset focuses on a specific capability — from long-context reasoning and factual grounding to STEM explanations, math Q&A, and polite multilingual interaction.
🌍 Explore the full collection on Hugging Face:
👉 lamhieu/xllms-66cdfe34307bb2edc8c6df7d
💬 Highlight: xLLMs – Dialogue Pubs
A large-scale multilingual dataset built from document-guided synthetic dialogues (Wikipedia, WikiHow, and technical sources). It’s ideal for training models on long-context reasoning, multi-turn coherence, and tool-augmented dialogue across 9 languages.
👉 lamhieu/xllms_dialogue_pubs
🧠 Designed for:
- Long-context and reasoning models
- Multilingual assistants
- Tool-calling and structured response learning
All datasets are open for research and development use — free, transparent, and carefully curated to improve dialogue model quality.