DD-DuDa / BitDistiller
[ACL 2024] A novel QAT with Self-Distillation framework to enhance ultra low-bit LLMs.
☆105Updated 9 months ago
Alternatives and similar repositories for BitDistiller:
Users that are interested in BitDistiller are comparing it to the libraries listed below
- Official PyTorch implementation of FlatQuant: Flatness Matters for LLM Quantization☆108Updated last month
- QQQ is an innovative and hardware-optimized W4A8 quantization solution for LLMs.☆107Updated 3 weeks ago
- QAQ: Quality Adaptive Quantization for LLM KV Cache☆47Updated 11 months ago
- The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…☆48Updated 2 years ago
- Code Repository of Evaluating Quantized Large Language Models☆116Updated 6 months ago
- An easy-to-use package for implementing SmoothQuant for LLMs☆94Updated 9 months ago
- The official implementation of the EMNLP 2023 paper LLM-FP4☆187Updated last year
- An algorithm for weight-activation quantization (W4A4, W4A8) of LLMs, supporting both static and dynamic quantization☆118Updated last month
- Official implementation of the EMNLP23 paper: Outlier Suppression+: Accurate quantization of large language models by equivalent and opti…☆47Updated last year
- AFPQ code implementation☆20Updated last year
- ☆120Updated last week
- ☆52Updated 11 months ago
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆298Updated 8 months ago
- ☆87Updated 6 months ago
- GEAR: An Efficient KV Cache Compression Recipefor Near-Lossless Generative Inference of LLM☆157Updated 8 months ago
- [ICML 2024] KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache☆279Updated last month
- Official implementation of the ICLR 2024 paper AffineQuant☆24Updated 11 months ago
- Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…☆58Updated last year
- This repository contains integer operators on GPUs for PyTorch.☆193Updated last year
- ☆52Updated 11 months ago
- ☆63Updated 3 months ago
- ☆62Updated last month
- Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".☆112Updated last year
- [NeurIPS 2024] The official implementation of "Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exitin…☆51Updated 8 months ago
- Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity☆201Updated last year
- The Official Implementation of Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference☆67Updated last month
- An innovative method expediting LLMs via streamlined semi-autoregressive generation and draft verification.☆24Updated last year
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆89Updated 2 weeks ago
- A quantization algorithm for LLM☆134Updated 8 months ago