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GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Paper • 2403.03507 • Published • 177 -
Flora: Low-Rank Adapters Are Secretly Gradient Compressors
Paper • 2402.03293 • Published • 4 -
PRILoRA: Pruned and Rank-Increasing Low-Rank Adaptation
Paper • 2401.11316 • Published • 1 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 44
Collections
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Collections including paper arxiv:2403.03507
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GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Paper • 2403.03507 • Published • 177 -
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
Paper • 2205.05638 • Published • 3 -
The Power of Scale for Parameter-Efficient Prompt Tuning
Paper • 2104.08691 • Published • 7 -
In-Context Learning Demonstration Selection via Influence Analysis
Paper • 2402.11750 • Published • 2
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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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GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Paper • 2403.03507 • Published • 177 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 65 -
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
Paper • 2403.13372 • Published • 58 -
InternLM2 Technical Report
Paper • 2403.17297 • Published • 26