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Language Modeling

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ifrit98/pyramidal-recurrent-layer

Listen, Attend and Spell

https://github.com/iglu-contest/nlp-baselines-2022

Learning to Solve Voxel Building Embodied Tasks from Pixels and Natural Language Instructions

https://github.com/ikuto056/Estimating_Distance

ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network

https://github.com/iliaschalkidis/ELMo-keras

Deep contextualized word representations

https://github.com/ilyagusev/rulm

Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data

https://github.com/imagination-research/lbt

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

https://github.com/indrajeet95/Device-Placement-Optimization-with-Reinforcement-Learning

Device Placement Optimization with Reinforcement Learning

https://github.com/infini-ai-lab/sirius

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

https://github.com/infly-ai/inf-mllm

Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing

https://github.com/insait-institute/lm-evaluation-harness-bg

Language Models are Few-Shot Learners

https://github.com/instructlab/instructlab

LAB: Large-Scale Alignment for ChatBots

https://github.com/intel/handwritten-chinese-ocr-samples

Writer-Aware CNN for Parsimonious HMM-Based Offline Handwritten Chinese Text Recognition

https://github.com/intel/neural-speed

Efficient Streaming Language Models with Attention Sinks

https://github.com/intellabs/fastrag

REPLUG: Retrieval-Augmented Black-Box Language Models

https://github.com/intelligent-machine-learning/glake

LayerKV: Optimizing Large Language Model Serving with Layer-wise KV Cache Management

https://github.com/internlm/xtuner

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

https://github.com/inzva/turkish-glove

Unsupervised Cross-lingual Representation Learning at Scale

https://github.com/ipieter/universal-distillation

Masked Language Model Scoring

https://github.com/irmvlab/point-mamba

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/isabelline/Text_VAE_tf

Generating Sentences from a Continuous Space

https://github.com/ishalyminov/memn2n

End-To-End Memory Networks

https://github.com/isi-nlp/Zoph_RNN

Recurrent Neural Network Regularization

https://github.com/issam9/finetuning-bert-models-for-arabic-dialect-detection

DziriBERT: a Pre-trained Language Model for the Algerian Dialect

https://github.com/itsShnik/adaptively-finetuning-transformers

LXMERT: Learning Cross-Modality Encoder Representations from Transformers

https://github.com/itzpankajpanwar/Tree-transform

Tree Transformer: Integrating Tree Structures into Self-Attention

https://github.com/ivabojic/sleepqa

ELI5: Long Form Question Answering

https://github.com/iver56/audiomentations

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

https://github.com/iwangjian/ByteCup2018

Regularizing and Optimizing LSTM Language Models

https://github.com/j9650/CoDeepNEAT

Evolving Deep Neural Networks

https://github.com/jackaduma/ChatGLM-LoRA-RLHF-PyTorch

GLM: General Language Model Pretraining with Autoregressive Blank Infilling

https://github.com/jackaduma/LAS_Mandarin_PyTorch

Listen, Attend and Spell

https://github.com/jackbandy/bookcorpus-datasheet

The Pile: An 800GB Dataset of Diverse Text for Language Modeling

https://github.com/jackbandy/deep_learning_ulmfit

Universal Language Model Fine-tuning for Text Classification

https://github.com/jackjhliu/End-to-End-Mandarin-ASR

Listen, Attend and Spell

https://github.com/jackjhliu/Pytorch-End-to-End-ASR-on-TIMIT

Listen, Attend and Spell

https://github.com/jacksonwuxs/usablexai_llm

Studying Large Language Model Generalization with Influence Functions

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.