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Convolutional 2D Knowledge Graph Embeddings

, , , and . Proceedings of the AAAI Conference on Artificial Intelligence, (2018)

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8-bit Optimizers via Block-wise Quantization., , , and . ICLR, OpenReview.net, (2022)SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression., , , , , , , , and . ICLR, OpenReview.net, (2024)Training Transformers Together., , , , , , , and . CoRR, (2022)Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models., , , , , , and . CoRR, (2022)High Performance Natural Language Processing., , , , , and . EMNLP (Tutorial Abstracts), page 24-27. Association for Computational Linguistics, (2020)The case for 4-bit precision: k-bit Inference Scaling Laws., and . ICML, volume 202 of Proceedings of Machine Learning Research, page 7750-7774. PMLR, (2023)Training Transformers Together., , , , , , , and . NeurIPS (Competition and Demos), volume 176 of Proceedings of Machine Learning Research, page 335-342. PMLR, (2021)LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale., , , and . CoRR, (2022)Towards A Unified View of Sparse Feed-Forward Network in Pretraining Large Language Model., , , , and . EMNLP, page 15038-15061. Association for Computational Linguistics, (2023)The case for 4-bit precision: k-bit Inference Scaling Laws, and . (2022)cite arxiv:2212.09720.