Qualcomm-AI-research / FP8-quantization
☆146Updated 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:
- PyTorch extension for emulating FP8 data formats on standard FP32 Xeon/GPU hardware.☆110Updated 5 months ago
- This repository contains integer operators on GPUs for PyTorch.☆204Updated last year
- PyTorch emulation library for Microscaling (MX)-compatible data formats☆224Updated 3 weeks ago
- ☆204Updated 3 years ago
- ☆230Updated 2 years ago
- Fast Hadamard transform in CUDA, with a PyTorch interface☆187Updated 11 months ago
- ☆55Updated last year
- Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming☆96Updated 3 years ago
- llama INT4 cuda inference with AWQ☆54Updated 3 months ago
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆109Updated 10 months ago
- ☆76Updated 2 years ago
- Benchmark code for the "Online normalizer calculation for softmax" paper☆91Updated 6 years ago
- Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".☆119Updated last year
- The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…☆47Updated 2 years ago
- ☆202Updated 10 months ago
- ☆158Updated last year
- A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores☆51Updated last year
- Code Repository of Evaluating Quantized Large Language Models☆123Updated 8 months ago
- BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.☆52Updated 2 years ago
- play gemm with tvm☆91Updated last year
- ☆96Updated last year
- SparseTIR: Sparse Tensor Compiler for Deep Learning☆137Updated 2 years ago
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆92Updated last week
- Official implementation of the EMNLP23 paper: Outlier Suppression+: Accurate quantization of large language models by equivalent and opti…☆46Updated last year
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆248Updated 6 months ago
- ☆70Updated 3 months ago
- Official PyTorch implementation of "FlatQuant: Flatness Matters for LLM Quantization"☆127Updated last week
- [ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization☆94Updated 3 years ago
- ☆97Updated last year
- Fast low-bit matmul kernels in Triton☆299Updated this week