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🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).
[ECCV 2024] AdaLog: Post-Training Quantization for Vision Transformers with Adaptive Logarithm Quantizer
Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".
A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (p…
List of papers related to neural network quantization in recent AI conferences and journals.
The PyTorch implementation of Learned Step size Quantization (LSQ) in ICLR2020 (unofficial)
[ICCV 2023] RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers
[IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer
[TMLR] Official PyTorch implementation of paper "Quantization Variation: A New Perspective on Training Transformers with Low-Bit Precision"
A paper list of some recent Transformer-based CV works.
TabMap for high-performance tabular data analysis - Nature BME
A collection of awesome bio-foundation models, including protein, RNA, DNA, gene, single-cell, and so on.
Bi-Directional Equivariant Long-Range DNA Sequence Modeling
A novel approach to improve the safety of large language models, enabling them to transition effectively from unsafe to safe state.
A framework to evaluate the generalization capability of safety alignment for LLMs
Python interface to access reference genome features (such as genes, transcripts, and exons) from Ensembl
Official implementation for HyenaDNA, a long-range genomic foundation model built with Hyena
AI-based pathology predicts origins for cancers of unknown primary - Nature
[ACMMM 2024] Hybrid Cost Volume for Memory-Efficient Optical Flow
[TPAMI 2025] IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching
The calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)