Md Hasan (mdhasanai)

mdhasanai

Geek Repo

Company:Friedrich Alexander University (FAU)

Location:Nuremberg, Bavaria, Germany

Home Page:https://mdhasanai.github.io

Twitter:@mdhasanai

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Md Hasan's repositories

Bangla-Word2Vec

Bangla Word Embedding

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Birds-Species-Classifications-using-Transfer-Learning

Birds Species Classifications using Transfer Learning

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FAU-Data-Engineering-SS23

Template repository for the AMSE/SAKI course at FAU in SS2023

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Awesome-Incremental-Learning

Awesome Incremental Learning

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codellama

Inference code for CodeLlama models

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daattali.github.io

Dean Attali's website - R/Shiny Consultant

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Dynamic-convolution-Pytorch

Pytorch!!!Pytorch!!!Pytorch!!! Dynamic Convolution: Attention over Convolution Kernels (CVPR-2020)

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llama

Inference code for LLaMA models

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ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

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Python

All Algorithms implemented in Python

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pytorch-frn

Filter Response Normalization Layer in PyTorch

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TNN

TNN: developed by Tencent Youtu Lab and Guangying Lab, a lightweight and high-performance deep learning framework for mobile inference. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework. TNN:由腾讯优图实验室和光影实验室协同打造,移动端高性能、轻量级推理框架,同时拥有跨平台、高性能、模型压缩、代码裁剪等众多突出优势。TNN框架在原有Rapidnet、ncnn框架的基础上进一步加强了移动端设备的支持以及性能优化,同时也借鉴了业界主流开源框架高性能和良好拓展性的优点。目前TNN已经在手Q、微视、P图等应用中落地,欢迎大家参与协同共建,促进TNN推理框架进一步完善。

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Verba

Retrieval Augmented Generation (RAG) chatbot powered by Weaviate

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vscode-python-template

A template for a dockerized Python development environment for VScode

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