Gather research papers, corresponding codes (if having), reading notes and any other related materials about Hot🔥🔥🔥 fields in Computer Vision based on Deep Learning.
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Updated
Jun 5, 2024
Gather research papers, corresponding codes (if having), reading notes and any other related materials about Hot🔥🔥🔥 fields in Computer Vision based on Deep Learning.
[CVPR 2024] DeepCache: Accelerating Diffusion Models for Free
[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
分享高质量的AI项目
Characterization study repository for pruning, a popular way to compress a DL model. this repo also investigates optimal sparse tensor layouts for pruned nets
On-device LLM Inference Powered by X-Bit Quantization
Simpler Distil-Whisper
List of papers related to neural network quantization in recent AI conferences and journals.
a collection of computer vision projects&tools. 计算机视觉方向项目和工具集合。
This repo contains model compression(using TensorRT) and documentation of running various deep learning models on NVIDIA Jetson Orin, Nano (aarch64 architectures)
ptdeco is a library for model optimization by decomposition built on top of PyTorch
Awesome Knowledge Distillation
A curated list of awesome NLP, Computer Vision, Model Compression, XAI, Reinforcement Learning, Security etc Paper
Dive into advanced quantization techniques. Learn to implement and customize linear quantization functions, measure quantization error, and compress model weights using PyTorch for efficient and accessible AI models.
Hyperparameter Tuning with Microsoft NNI to automated machine learning (AutoML) experiments. The tool dispatches and runs trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different environments like local machine, remote servers and cloud.
[CVPR 2024 Highlight] Logit Standardization in Knowledge Distillation
Resources of our survey paper "Enabling AI on Edges: Techniques, Applications and Challenges"
模型压缩的小白入门教程
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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