Ilya Palachev (ilya-palachev)

ilya-palachev

Geek Repo

Company:@Samsung

Location:Russia, Moscow

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Ilya Palachev's repositories

awesome-ai-compilers

My survey of literature on compilers for AI models

polyhedra-correction-library

Code of my qualification and PhD works: reconstruction and correction of 3D polyhedra from shadow contours

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awesome-polyhedra-recovery

A curated list of awesome papers about polyhedra recovery

Awesome-Korean-NLP

A curated list of resources for NLP (Natural Language Processing) for Korean

awesome-machine-learning-in-compilers

Must read research papers and links to tools and datasets that are related to using machine learning for compilers and systems optimisation

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awesome-seml

A curated list of articles that cover the software engineering best practices for building machine learning applications.

AwesomeKorean_Data

한국어 데이터 세트 링크

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bert-stack-overflow

Train a BERT model with TensorFlow 2.0 to automatically tag StackOverflow questions!

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code-completion

pytorch version of code completion with neural attention and pointer networks

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CodeBERT

CodeBERT

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DistilKoBERT

Distillation of KoBERT from SKTBrain (Lightweight KoBERT)

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github-api

Java API for GitHub

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HanBert-Transformers

HanBert on 🤗 Huggingface Transformers 🤗

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KoBERT

Korean BERT pre-trained cased (KoBERT)

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KoELECTRA

Pretrained ELECTRA Model for Korean

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KoGPT2

Korean GPT-2 pretrained cased (KoGPT2)

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korbert-mecab-multigpu

MULTI GPU환경에서 ETRI 한국어 BERT모델 활용한 Korquad 학습 방법

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KR-BERT

KoRean based BERT pre-trained models (KR-BERT) for Tensorflow and PyTorch

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multiatis

Data and code for the paper "End-to-End Slot Alignment and Recognition for Cross-Lingual NLU" (Accepted to EMNLP 2020)

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Revisar

Learning Quick Fixes from Code Repositories

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awesome-machine-learning-on-source-code

Cool links & research papers related to Machine Learning applied to source code (MLonCode)

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combirepo

The tool for creation Tizen firmware from combination of different repositories

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CppCoreGuidelines

The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++

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demo

🤖 Fork me to try out Dependabot

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intro-to-dl

Resources for "Introduction to Deep Learning" course.

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