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Collections including paper arxiv:2402.17764
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 572 -
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
Paper • 2310.19102 • Published • 7 -
AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning
Paper • 2311.00257 • Published • 8 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 48
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Scaling Instruction-Finetuned Language Models
Paper • 2210.11416 • Published • 5 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 132 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 51 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 59
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