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Apr 23
Apr 23
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Collections including paper arxiv:2402.17764
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6 days ago
6 days ago
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 572 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 94 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 102 -
TransformerFAM: Feedback attention is working memory
Paper • 2404.09173 • Published • 42
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Apr 8
Apr 8
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Apr 2
Apr 2
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DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
Paper • 1606.06160 • Published • 1 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 572 -
mobiuslabsgmbh/Llama-2-7b-chat-hf_1bitgs8_hqq
Text Generation • Updated • 54 • 74
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Apr 1
Apr 1
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May 9
May 9
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Jamba: A Hybrid Transformer-Mamba Language Model
Paper • 2403.19887 • Published • 99 -
sDPO: Don't Use Your Data All at Once
Paper • 2403.19270 • Published • 32 -
ViTAR: Vision Transformer with Any Resolution
Paper • 2403.18361 • Published • 48 -
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
Paper • 2403.18814 • Published • 42
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Mar 31
Mar 31
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Mar 31
Mar 31
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Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing
Paper • 2306.12929 • Published • 11 -
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models
Paper • 2309.02784 • Published • 1 -
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models
Paper • 2310.08041 • Published • 1 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 572
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Mar 29
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Mar 28
Mar 28