Build, customize and control you own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6
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Updated
Mar 31, 2024 - Python
Build, customize and control you own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6
Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP
Microsoft Automatic Mixed Precision Library
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
High Resolution Style Transfer in PyTorch with Color Control and Mixed Precision 🎨
Training with FP16 weights in PyTorch
A tool for debugging and assessing floating point precision and reproducibility.
基于tensorflow1.x的预训练模型调用,支持单机多卡、梯度累积,XLA加速,混合精度。可灵活训练、验证、预测。
<케라스 창시자에게 배우는 딥러닝 2판> 도서의 코드 저장소
BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.
🎯 Accumulated Gradients for TensorFlow 2
FP64 equivalent GEMM via Int8 Tensor Cores using the Ozaki scheme
CMix-NN: Mixed Low-Precision CNN Library for Memory-Constrained Edge Devices
PDPU: An Open-Source Posit Dot-Product Unit for Deep Learning Applications
An implementation of HPL-AI Mixed-Precision Benchmark based on hpl-2.3
PyCon SG 2019 Tutorial: Optimizing TensorFlow Performance
Extremely simple and understandable GPT2 implementation with minor tweaks
This is the open source version of HPL-MXP. The code performance has been verified on Frontier
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