facebookresearch / LLM-QATLinks
Code repo for the paper "LLM-QAT Data-Free Quantization Aware Training for Large Language Models"
☆312Updated 6 months ago
Alternatives and similar repositories for LLM-QAT
Users that are interested in LLM-QAT are comparing it to the libraries listed below
Sorting:
- The official implementation of the EMNLP 2023 paper LLM-FP4☆214Updated last year
- This repository contains integer operators on GPUs for PyTorch.☆216Updated last year
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆320Updated last year
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆381Updated last year
- Code repo for the paper "SpinQuant LLM quantization with learned rotations"☆326Updated 7 months ago
- ☆335Updated last year
- ☆154Updated 2 years ago
- Code for Neurips24 paper: QuaRot, an end-to-end 4-bit inference of large language models.☆424Updated 9 months ago
- [ICML 2024] KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache☆323Updated 8 months ago
- An easy-to-use package for implementing SmoothQuant for LLMs☆106Updated 5 months ago
- [ICML 2025] Official PyTorch implementation of "FlatQuant: Flatness Matters for LLM Quantization"☆162Updated last month
- A repository dedicated to evaluating the performance of quantizied LLaMA3 using various quantization methods..☆194Updated 8 months ago
- [ACL 2024] A novel QAT with Self-Distillation framework to enhance ultra low-bit LLMs.☆122Updated last year
- [NeurIPS'23] H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.☆473Updated last year
- Spec-Bench: A Comprehensive Benchmark and Unified Evaluation Platform for Speculative Decoding (ACL 2024 Findings)☆311Updated 4 months ago
- Awesome list for LLM quantization☆302Updated this week
- An algorithm for weight-activation quantization (W4A4, W4A8) of LLMs, supporting both static and dynamic quantization☆148Updated 3 months ago
- Reorder-based post-training quantization for large language model☆195Updated 2 years ago
- [NeurIPS 2022] A Fast Post-Training Pruning Framework for Transformers☆191Updated 2 years ago
- QQQ is an innovative and hardware-optimized W4A8 quantization solution for LLMs.☆139Updated 3 weeks ago
- Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".☆126Updated 2 years ago
- ☆199Updated 4 months ago
- ☆228Updated last year
- A quantization algorithm for LLM☆142Updated last year
- Official PyTorch implementation of QA-LoRA☆140Updated last year
- Microsoft Automatic Mixed Precision Library☆619Updated 11 months ago
- [NeurIPS 2024] The official implementation of "Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exitin…☆59Updated last year
- For releasing code related to compression methods for transformers, accompanying our publications☆444Updated 8 months ago
- [ICLR 2025] COAT: Compressing Optimizer States and Activation for Memory-Efficient FP8 Training☆239Updated last month
- Implementation of Speculative Sampling as described in "Accelerating Large Language Model Decoding with Speculative Sampling" by Deepmind☆100Updated last year