https://github.com/macaronlin/llama3-quantization
공식 코드An empirical study of LLaMA3 quantization: from LLMs to MLLMs
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A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.
Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.
Source: Wikipedia
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
An empirical study of LLaMA3 quantization: from LLMs to MLLMs
Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP
Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers
PsycoLLM: Enhancing LLM for Psychological Understanding and Evaluation
Neural Language Modeling for Contextualized Temporal Graph Generation
Video Moment Localization using Object Evidence and Reverse Captioning
CORAL: Expert-Curated medical Oncology Reports to Advance Language Model Inference
QueerBench: Quantifying Discrimination in Language Models Toward Queer Identities
Knowledge-enhanced Visual-Language Pretraining for Computational Pathology
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation
Cognate Transformer for Automated Phonological Reconstruction and Cognate Reflex Prediction
JoFormer (Journey-based Transformer): Theory and Empirical Analysis on the Tiny Shakespeare Dataset
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model
Unknown Prompt, the only Lacuna: Unveiling CLIP's Potential for Open Domain Generalization
Low-resource Bilingual Dialect Lexicon Induction with Large Language Models
ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domain
Stance Reasoner: Zero-Shot Stance Detection on Social Media with Explicit Reasoning
Topology-aware Debiased Self-supervised Graph Learning for Recommendation
Evaluating Document Representations for Content-based Legal Literature Recommendations
Enriching BERT with Knowledge Graph Embeddings for Document Classification
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings
FIDAVL: Fake Image Detection and Attribution using Vision-Language Model
CLMSM: A Multi-Task Learning Framework for Pre-training on Procedural Text
Information Guided Regularization for Fine-tuning Language Models
Laying Anchors: Semantically Priming Numerals in Language Modeling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.