Models
Datasets
Spaces
Posts
Docs
Enterprise
Pricing
Log In
Sign Up

Collections

Discover the best community collections!

Collections including paper arxiv:2402.04291

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48
OneBit: Towards Extremely Low-bit Large Language Models

Paper • 2402.11295 • Published Feb 17 • 23
A Survey on Transformer Compression

Paper • 2402.05964 • Published Feb 5
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers

Paper • 2402.08958 • Published Feb 14 • 3

Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

Paper • 2401.08417 • Published Jan 16 • 33
PIXART-δ: Fast and Controllable Image Generation with Latent Consistency Models

Paper • 2401.05252 • Published Jan 10 • 47
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48
FiT: Flexible Vision Transformer for Diffusion Model

Paper • 2402.12376 • Published Feb 19 • 48

HensonResearchFor1BitLLMs

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

Paper • 2402.17764 • Published Feb 27 • 602
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving

Paper • 2310.19102 • Published Oct 29, 2023 • 10
AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning

Paper • 2311.00257 • Published Nov 1, 2023 • 8
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29 • 52
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Paper • 2403.03507 • Published Mar 6 • 182
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 602

BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15 • 18
OneBit: Towards Extremely Low-bit Large Language Models

Paper • 2402.11295 • Published Feb 17 • 23
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48
GPTVQ: The Blessing of Dimensionality for LLM Quantization

Paper • 2402.15319 • Published Feb 23 • 19

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15 • 100
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 39
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15 • 18
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15 • 36

Quantization techniques

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 602

Quantization | Compression

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6 • 48
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization

Paper • 2401.18079 • Published Jan 31 • 7
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers

Paper • 2402.08958 • Published Feb 14 • 3
OneBit: Towards Extremely Low-bit Large Language Models

Paper • 2402.11295 • Published Feb 17 • 23

Previous
1
2
3
Next

Company

© Hugging Face

TOS Privacy About Jobs

Website

Models Datasets Spaces Pricing Docs