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Hieu Lam
lamhieu
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π 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 β from long-context reasoning and factual grounding to STEM explanations, math Q&A, and polite multilingual interaction. π Explore the full collection on Hugging Face: π https://huggingface.co/collections/lamhieu/xllms-66cdfe34307bb2edc8c6df7d π¬ Highlight: xLLMs β Dialogue Pubs A large-scale multilingual dataset built from document-guided synthetic dialogues (Wikipedia, WikiHow, and technical sources). Itβs ideal for training models on long-context reasoning, multi-turn coherence, and tool-augmented dialogue across 9 languages. π https://huggingface.co/datasets/lamhieu/xllms_dialogue_pubs π§ Designed for: - Long-context and reasoning models - Multilingual assistants - Tool-calling and structured response learning All datasets are open for research and development use β free, transparent, and carefully curated to improve dialogue model quality.
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lamhieu/lightweight-embeddings
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lamhieu/naturalqa_dialogue_vi
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May 17, 2024
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lamhieu/wikipedia_dialogue_vi
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May 17, 2024
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lamhieu/wikihow_dialogue_vi
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May 17, 2024
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lamhieu/alpaca_gpt4_dialogue_en
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May 15, 2024
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lamhieu/alpaca_gpt4_dialogue_vi
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May 15, 2024
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lamhieu/alpaca_multiturns_dialogue_vi
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May 15, 2024
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lamhieu/translate_tinystories_dialogue_envi
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May 15, 2024
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