Collection by
Jan 5
Jan 5
Collections
Discover the best community collections!
Collections including paper arxiv:2311.09179
Collection by
Jun 21
Jun 21
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QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models
Paper • 2310.16795 • Published • 26 -
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
Paper • 2308.12066 • Published • 4 -
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference
Paper • 2303.06182 • Published • 1 -
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate
Paper • 2112.14397 • Published • 1
Collection by
Nov 17, 2023
Nov 17, 2023
Collection by
Feb 19
Feb 19
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S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Paper • 2311.03285 • Published • 28 -
Tailoring Self-Rationalizers with Multi-Reward Distillation
Paper • 2311.02805 • Published • 3 -
Ultra-Long Sequence Distributed Transformer
Paper • 2311.02382 • Published • 2 -
OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
Paper • 2309.11235 • Published • 16
Collection by
Sep 17
Sep 17
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PockEngine: Sparse and Efficient Fine-tuning in a Pocket
Paper • 2310.17752 • Published • 12 -
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Paper • 2311.03285 • Published • 28 -
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Paper • 2311.06243 • Published • 17 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 28
Collection by
Sep 23
Sep 23
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Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time
Paper • 2310.17157 • Published • 11 -
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
Paper • 2305.15805 • Published • 1 -
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt
Paper • 2305.11186 • Published • 1 -
Composable Sparse Fine-Tuning for Cross-Lingual Transfer
Paper • 2110.07560 • Published • 1
Collection by
Jul 9
Jul 9
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QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models
Paper • 2310.16795 • Published • 26 -
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
Paper • 2308.12066 • Published • 4 -
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference
Paper • 2303.06182 • Published • 1 -
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate
Paper • 2112.14397 • Published • 1
Collection by
Jul 8
Jul 8
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LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Paper • 2310.08659 • Published • 22 -
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 44 -
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
Paper • 2309.16119 • Published • 1 -
LoRA ensembles for large language model fine-tuning
Paper • 2310.00035 • Published • 2
Collection by
Nov 16, 2023
Nov 16, 2023