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Language Modeling

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코드

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

https://github.com/the-finai/pixiu

PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance

https://github.com/theQuert/inlpfun

Semi-supervised Sequence Learning

https://github.com/thearkaprava/ms-temba

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/thecodemasterk/BERT

Semi-supervised Sequence Learning

https://github.com/thibaultdouzon/long-range-document-transformer

cosFormer: Rethinking Softmax in Attention

https://github.com/thisiskhan/tensorflow-developer-certificate-machine-learning-kit

Universal Language Model Fine-tuning for Text Classification

https://github.com/thomasvengal/deeplearning

Where to put the Image in an Image Caption Generator

https://github.com/thomlake/pytorch-attention

End-To-End Memory Networks

https://github.com/thompsonj/nanoGCG

Query-Based Adversarial Prompt Generation

https://github.com/thoppe/personal_cv

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

https://github.com/threelittlemonkeys/pointer-network-pytorch

Order Matters: Sequence to sequence for sets

https://github.com/thu-coai/CDial-GPT

The Curious Case of Neural Text Degeneration

https://github.com/thu-esis/jiuzhou

TagRouter: Learning Route to LLMs through Tags for Open-Domain Text Generation Tasks

https://github.com/thu-keg/korc

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

https://github.com/thudm/alignbench

CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation

https://github.com/thudm/chatglm

GLM: General Language Model Pretraining with Autoregressive Blank Infilling

https://github.com/thudm/chatglm2-6b

GLM: General Language Model Pretraining with Autoregressive Blank Infilling

https://github.com/thudm/chatglm3

GLM: General Language Model Pretraining with Autoregressive Blank Infilling

https://github.com/thudm/swissarmytransformer

Prefix-Tuning: Optimizing Continuous Prompts for Generation

https://github.com/thudm/visualglm-6b

GLM: General Language Model Pretraining with Autoregressive Blank Infilling

https://github.com/thunlp-mt/promptgating4mctg

Reducing Transformer Depth on Demand with Structured Dropout

https://github.com/thunlp/clueanchor

Atlas: Few-shot Learning with Retrieval Augmented Language Models

https://github.com/tianbaochou/CNAS

DARTS: Differentiable Architecture Search

https://github.com/tianhai123/vit-pytorch

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

https://github.com/tianyic/only_train_once

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

https://github.com/tigerresearch/tigerbot

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

https://github.com/tighu20/Kaggle-Tweet-Sentiment-Extraction

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/tihonovcore/model

Structural Language Models of Code

https://github.com/timbmg/Sentence-VAE

Generating Sentences from a Continuous Space

https://github.com/timdettmers/bitsandbytes

8-bit Optimizers via Block-wise Quantization

https://github.com/timonziegenbein/inappropriateness-mitigation

LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback

https://github.com/tinhb92/rnn_darts_fastai

DARTS: Differentiable Architecture Search

https://github.com/titu1994/neural-architecture-search

Neural Architecture Search with Reinforcement Learning

https://github.com/tjdevWorks/TEASEL

TEASEL: A Transformer-Based Speech-Prefixed Language Model

https://github.com/tlc-pack/libflash_attn

FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

https://github.com/tmatha/lstm

Recurrent Neural Network Regularization

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