KornWtp's repositories

MixSP

MixSP: Space Decomposition for Sentence Embedding (ACL)

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ejtraderMT

Metatrader 5 API - Trading and history OHLC Dataframe in Nano Seconds

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ConGen

Implementation of ConGen: Unsupervised Control and Generalization Distillation For Sentence Representation (Finding of EMNLP 2022).

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Thai-Sentence-Vector-Benchmark

Benchmark for Thai sentence representation

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NLP_2023

NLP course @ chula 2023

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allennlp

An open-source NLP research library, built on PyTorch.

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SimCSE-1

EMNLP'2021: SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821

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CharacterBERT-DR

The offcial repository for 'CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos', SIGIR2022

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pattern_2022

Pattern recognition course 2022 @ Chulalongkorn University

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Self_Supervised_CWS

This project has included related source codes and datasets of our EMNLP2021 paper

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trans-encoder

Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations

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ConSERT

Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer

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machine-learning-courses

A collection of machine learning courses.

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pytorch-seq2seq

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

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pytorch-Deep-Learning

Deep Learning (with PyTorch)

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pytorch-image-classification

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

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sentence-transformers

Multilingual Sentence & Image Embeddings with BERT

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BERT-flow

TensorFlow implementation of On the Sentence Embeddings from Pre-trained Language Models (EMNLP 2020)

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pytorch-sentiment-analysis

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

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a-tour-of-pytorch-optimizers

A tour of different optimization algorithms in PyTorch.

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SentEval

A python tool for evaluating the quality of sentence embeddings.

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natural-language-processing

Codes, datasets, and explanations for some basic natural language tasks and models.

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