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Collections

Discover the best community collections!

Collections including paper arxiv:2404.14047

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

Paper • 2402.17764 • Published Feb 27, 2024 • 605
BitNet: Scaling 1-bit Transformers for Large Language Models

Paper • 2310.11453 • Published Oct 17, 2023 • 96
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 104
TransformerFAM: Feedback attention is working memory

Paper • 2404.09173 • Published Apr 14, 2024 • 43

XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference

Paper • 2404.15420 • Published Apr 23, 2024 • 7
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework

Paper • 2404.14619 • Published Apr 22, 2024 • 126
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22, 2024 • 253
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 44

Specific Models

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22, 2024 • 253
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 44
Octopus v4: Graph of language models

Paper • 2404.19296 • Published Apr 30, 2024 • 116

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 44

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22, 2024 • 253
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 44
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 605

Papers - Llama 3 - GPTQ AWQ PB-LLM BiLLM - 1.1-8 bits LoRA

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 44

Papers - Llama 3 - Fine-tuning

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 44
LiteSearch: Efficacious Tree Search for LLM

Paper • 2407.00320 • Published Jun 29, 2024 • 37
Cut Your Losses in Large-Vocabulary Language Models

Paper • 2411.09009 • Published Nov 13, 2024 • 43
LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models

Paper • 2411.09595 • Published Nov 14, 2024 • 71

Papers - Llama 3 - Fine-tuning - Quantization

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 44

Papers - Llama 3

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 44
Reasoning in Large Language Models: A Geometric Perspective

Paper • 2407.02678 • Published Jul 2, 2024 • 1
Natural Language Reinforcement Learning

Paper • 2411.14251 • Published Nov 21, 2024 • 28
Byte Latent Transformer: Patches Scale Better Than Tokens

Paper • 2412.09871 • Published 24 days ago • 83

LLaMA3-Quantization

This is the official quantized models collection of “How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study”

Efficient-ML/LLaMA-3-8B-GPTQ-4bit-b128

Updated Apr 21, 2024 • 3
Efficient-ML/LLaMA-3-8B-SmoothQuant-4bit-4bit

Text Generation • Updated Apr 22, 2024 • 14
Efficient-ML/LLaMA-3-8B-AWQ-4bit-b128

Text Generation • Updated Apr 28, 2024 • 8
Efficient-ML/LLaMA-3-8B-SmoothQuant-8bit-8bit

Text Generation • Updated Apr 22, 2024 • 15

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