Collections
Discover the best community collections!
Collections including paper arxiv:2305.14314
-
QLoRA: Efficient Finetuning of Quantized LLMs
Paper • 2305.14314 • Published • 45 -
EfficientQAT: Efficient Quantization-Aware Training for Large Language Models
Paper • 2407.11062 • Published • 8 -
Spectra: A Comprehensive Study of Ternary, Quantized, and FP16 Language Models
Paper • 2407.12327 • Published • 76
-
ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 14 -
Attention Is All You Need
Paper • 1706.03762 • Published • 41 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 14 -
Jamba: A Hybrid Transformer-Mamba Language Model
Paper • 2403.19887 • Published • 103
-
Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 83 -
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Paper • 2404.10667 • Published • 15 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 24 -
DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 25
-
A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity
Paper • 2401.01967 • Published -
Secrets of RLHF in Large Language Models Part I: PPO
Paper • 2307.04964 • Published • 27 -
Zephyr: Direct Distillation of LM Alignment
Paper • 2310.16944 • Published • 120 -
LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
Paper • 2404.05961 • Published • 64
-
Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning
Paper • 2310.20587 • Published • 16 -
SELF: Language-Driven Self-Evolution for Large Language Model
Paper • 2310.00533 • Published • 2 -
QLoRA: Efficient Finetuning of Quantized LLMs
Paper • 2305.14314 • Published • 45 -
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 43
-
QLoRA: Efficient Finetuning of Quantized LLMs
Paper • 2305.14314 • Published • 45 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 592 -
Breaking Boundaries: Investigating the Effects of Model Editing on Cross-linguistic Performance
Paper • 2406.11139 • Published • 12