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Collections including paper arxiv:2402.17764

towards-embedded-foundational-models

meta-llama/Llama-2-7b-chat-hf

Text Generation • Updated Apr 17 • 1.04M • 3.62k
ibm-granite/granite-8b-code-instruct

Text Generation • Updated May 10 • 10.5k • 93
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 571
Running

118

🏆

Low-bit Quantized Open LLM Leaderboard

Track, rank and evaluate open LLMs and chatbots

Dom Per Andersson

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 571

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 571
BitNet: Scaling 1-bit Transformers for Large Language Models

Paper • 2310.11453 • Published Oct 17, 2023 • 94
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2 • 102
TransformerFAM: Feedback attention is working memory

Paper • 2404.09173 • Published Apr 14 • 42

Running

7

📊

OpenWakeWord
xai-org/grok-1

Text Generation • Updated Mar 28 • 1.79k • 2.12k
databricks/dbrx-instruct

Text Generation • Updated Apr 19 • 175k • 1.08k
mistralai/Mistral-7B-Instruct-v0.2

Text Generation • Updated Mar 24 • 1.16M • 2.38k

DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Paper • 1606.06160 • Published Jun 20, 2016 • 1
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 571
mobiuslabsgmbh/Llama-2-7b-chat-hf_1bitgs8_hqq

Text Generation • Updated Mar 27 • 68 • 74

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 571

Jamba: A Hybrid Transformer-Mamba Language Model

Paper • 2403.19887 • Published Mar 28 • 99
sDPO: Don't Use Your Data All at Once

Paper • 2403.19270 • Published Mar 28 • 32
ViTAR: Vision Transformer with Any Resolution

Paper • 2403.18361 • Published Mar 27 • 48
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Paper • 2403.18814 • Published Mar 27 • 42

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 571

Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing

Paper • 2306.12929 • Published Jun 22, 2023 • 11
Norm Tweaking: High-performance Low-bit Quantization of Large Language Models

Paper • 2309.02784 • Published Sep 6, 2023 • 1
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models

Paper • 2310.08041 • Published Oct 12, 2023 • 1
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 571

Inference efficiency

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 571

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