Papers with Code 아카이브

Language Modeling

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/facebookresearch/low-shot-shrink-hallucinate

Matching Networks for One Shot Learning

https://github.com/facebookresearch/meta_secalign

InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents

https://github.com/facebookresearch/metaicl

UnifiedQA: Crossing Format Boundaries With a Single QA System

https://github.com/facebookresearch/multihop_dense_retrieval

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

https://github.com/facebookresearch/multimodal

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

https://github.com/facebookresearch/perception_models

Perception Encoder: The best visual embeddings are not at the output of the network

https://github.com/facebookresearch/salina

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

https://github.com/facebookresearch/spartan

Top-KAST: Top-K Always Sparse Training

https://github.com/facebookresearch/three_bricks

A Watermark for Large Language Models

https://github.com/facebookresearch/wav2letter

Semi-Supervised Speech Recognition via Local Prior Matching

https://github.com/facebookresearch/wav2letter/tree/master/recipes/models/sota/2019

End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures

https://github.com/facebookresearch/xformers

Longformer: The Long-Document Transformer

https://github.com/facebookresearch/xformers/blob/main/xformers/ops/fmha/flash.py

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

https://github.com/facico/chinese-vicuna

Chinese-Vicuna: A Chinese Instruction-following Llama-based Model

https://github.com/faizansuhail89/bert

Semi-supervised Sequence Learning

https://github.com/fanchenyou/transformer-study

XLNet: Generalized Autoregressive Pretraining for Language Understanding

https://github.com/fancyerii/bert

Semi-supervised Sequence Learning

https://github.com/fangyiyu/Modified_MNIST_Classification

Language Modeling with Gated Convolutional Networks

https://github.com/fastai/fastai/blob/master/fastai/text/models/awdlstm.py

Regularizing and Optimizing LSTM Language Models

https://github.com/fawazsammani/knowing-when-to-look-adaptive-attention

Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning

https://github.com/fciannel/bert_fciannel

Semi-supervised Sequence Learning

https://github.com/feifeibear/llmspeculativesampling

Fast Inference from Transformers via Speculative Decoding

https://github.com/fengleifan/relinear

ReZero is All You Need: Fast Convergence at Large Depth

https://github.com/few-shot-NER-benchmark/BaselineCode

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/feyzaakyurek/XLM-LwLL

Cross-lingual Language Model Pretraining

https://github.com/fiveai/on-episodes-fsl

Matching Networks for One Shot Learning

https://github.com/fixie-ai/ultravox

AudioLM: a Language Modeling Approach to Audio Generation

https://github.com/fkodom/dilated-attention-pytorch

Foundation Transformers

https://github.com/fkodom/grouped-query-attention-pytorch

GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

https://github.com/fkodom/yet-another-retnet

A Length-Extrapolatable Transformer

https://github.com/flagopen/flaginstruct

Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

https://github.com/flairNLP/flair

Deep contextualized word representations

https://github.com/flexible-fl/flex-nlp

RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/float256/rectified-adam-keras

On the Variance of the Adaptive Learning Rate and Beyond

https://github.com/floleuerer/fastai_ulmfit

Universal Language Model Fine-tuning for Text Classification

https://github.com/floraxinru/HotelReviews_SentimentAnalysis

Universal Language Model Fine-tuning for Text Classification

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