☆169Mar 9, 2023Updated 2 years ago
Alternatives and similar repositories for FP8-quantization
Users that are interested in FP8-quantization are comparing it to the libraries listed below
Sorting:
- The official implementation of the EMNLP 2023 paper LLM-FP4☆220Dec 15, 2023Updated 2 years ago
- The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…☆49Oct 5, 2022Updated 3 years ago
- ☆209Nov 9, 2021Updated 4 years ago
- [IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer☆360Apr 11, 2023Updated 2 years ago
- Training with Block Minifloat number representation☆18May 2, 2021Updated 4 years ago
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,612Jul 12, 2024Updated last year
- ☆79Jul 21, 2022Updated 3 years ago
- This repository contains integer operators on GPUs for PyTorch.☆237Sep 29, 2023Updated 2 years ago
- Code repo for the paper "LLM-QAT Data-Free Quantization Aware Training for Large Language Models"☆321Mar 4, 2025Updated 11 months ago
- AFPQ code implementation☆23Nov 6, 2023Updated 2 years ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆277Jul 16, 2025Updated 7 months ago
- PyTorch implementation of "Deep Transferring Quantization" (ECCV2020)☆18Jun 22, 2022Updated 3 years ago
- Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. In CVPR 2022.☆138Apr 28, 2022Updated 3 years ago
- A quantization algorithm for LLM☆148Jun 21, 2024Updated last year
- Post-Training Quantization for Vision transformers.☆238Jul 19, 2022Updated 3 years ago
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆336Jul 2, 2024Updated last year
- Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.☆453May 15, 2023Updated 2 years ago
- The PyTorch implementation of Learned Step size Quantization (LSQ) in ICLR2020 (unofficial)☆139Nov 19, 2020Updated 5 years ago
- ☆25Dec 11, 2021Updated 4 years ago
- Quantization in the Jagged Loss Landscape of Vision Transformers☆13Oct 22, 2023Updated 2 years ago
- Official implementation of the EMNLP23 paper: Outlier Suppression+: Accurate quantization of large language models by equivalent and opti…☆50Oct 21, 2023Updated 2 years ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆37Aug 20, 2024Updated last year
- Microsoft Automatic Mixed Precision Library☆636Dec 1, 2025Updated 3 months ago
- [ICML'21 Oral] I-BERT: Integer-only BERT Quantization☆265Jan 29, 2023Updated 3 years ago
- IntLLaMA: A fast and light quantization solution for LLaMA☆18Jul 21, 2023Updated 2 years ago
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆402Aug 13, 2024Updated last year
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆28Dec 6, 2023Updated 2 years ago
- PyTorch emulation library for Microscaling (MX)-compatible data formats☆343Jun 18, 2025Updated 8 months ago
- PyTorch implementation of Data Free Quantization Through Weight Equalization and Bias Correction.☆263Oct 3, 2023Updated 2 years ago
- Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming☆98Jun 10, 2021Updated 4 years ago
- BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.☆751Aug 6, 2025Updated 6 months ago
- ☆41Mar 28, 2024Updated last year
- super-resolution; post-training quantization; model compression☆14Nov 10, 2023Updated 2 years ago
- Benchmark tests supporting the TiledCUDA library.☆18Nov 19, 2024Updated last year
- Fast Hadamard transform in CUDA, with a PyTorch interface☆285Oct 19, 2025Updated 4 months ago
- QONNX: Arbitrary-Precision Quantized Neural Networks in ONNX☆178Feb 19, 2026Updated last week
- ☆85Jan 23, 2025Updated last year
- [ICCV 2023] Q-Diffusion: Quantizing Diffusion Models.☆370Mar 21, 2024Updated last year
- SOTA low-bit LLM quantization (INT8/FP8/MXFP8/INT4/MXFP4/NVFP4) & sparsity; leading model compression techniques on PyTorch, TensorFlow, …☆2,590Updated this week