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Alfaxad Eyembe

Alfaxad
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https://alfaxad.com

AI & ML interests

AI, Robotics

Recent Activity

liked a dataset 2 days ago
CraneAILabs/wildjailbreak-africa
upvoted an article 12 days ago
Welcome GPT OSS, the new open-source model family from OpenAI!
reacted to prithivMLmods's post with ā¤ļø 12 days ago
On the verge of releasing Poseidon-Reasoning-5M, a dataset built to excel in general thought processes, mathematics, and science across a diverse mixture of domains, Iā€™m also dropping the Gargantua-R1-Compact dataset, a collection of over six million high-quality reasoning QA pair traces. šŸ¤—šŸš€ āœ¦ Gargantua-R1-Compact : https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Compact ``` from datasets import load_dataset dataset = load_dataset("prithivMLmods/Gargantua-R1-Compact", split="train") ``` Additionally, Iā€™m adding the mini version of Gargantua ā€” the Gargantua-R1-Wee : https://huggingface.co/datasets/prithivMLmods/Gargantua-R1-Wee ``` from datasets import load_dataset dataset = load_dataset("prithivMLmods/Gargantua-R1-Wee", split="train") ``` The composition spans 73.93% core mathematical reasoning involving problems, proofs, and computational challenges, 12.11% across diverse scientific domains such as physics, chemistry, biology, and interdisciplinary topics, 11.35% in competitive coding covering algorithms and data structures, 1.37% in academic science focusing on research-level methodology, 0.95% in creative and analytical reasoning through logic puzzles and problem-solving tasks, 0.25% in specialized technical areas like MLOps, LLMs, diffusion models, and CUDA, and 0.06% involving data from graphs and charts converted into structured JSON formats. Designed with both rich contextual depth and formal structural clarity, Gargantua-R1-Compact is an optimal resource for advancing research in symbolic reasoning, interpretability, and high-precision question answering in mathematical domains. āœ¦ Collection : https://huggingface.co/collections/prithivMLmods/gargantua-r1-mod-6896bfd7834e82b89ad2b38b To know more about it, visit the dataset card of the respective dataset. !!
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