https://github.com/eleutherai/nanogpt-mup
공식 코드Sparse maximal update parameterization: A holistic approach to sparse training dynamics
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
Sparse maximal update parameterization: A holistic approach to sparse training dynamics
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
Automatically Interpreting Millions of Features in Large Language Models
Balancing Label Quantity and Quality for Scalable Elicitation
Zeroth-Order Adaptive Neuron Alignment Based Pruning without Re-Training
MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Classification and Detection
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis
Coordinate-Aware Thermal Infrared Tracking Via Natural Language Modeling
Improving Lemmatization of Non-Standard Languages with Joint Learning
Improving Lemmatization of Non-Standard Languages with Joint Learning
How transformers learn structured data: insights from hierarchical filtering
Emergent Linguistic Structures in Neural Networks are Fragile
Exploring the Syntactic Abilities of RNNs with Multi-task Learning
ChatCounselor: A Large Language Models for Mental Health Support
Non-autoregressive Error Correction for CTC-based ASR with Phone-conditioned Masked LM
Leveraging Large Language Models for Automated Dialogue Analysis
GIST: Generating Image-Specific Text for Fine-grained Object Classification
CoditT5: Pretraining for Source Code and Natural Language Editing
A Tool for Generating Exceptional Behavior Tests With Large Language Models
Regulation of Language Models With Interpretability Will Likely Result In A Performance Trade-Off
Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling
Fly-Swat or Cannon? Cost-Effective Language Model Choice via Meta-Modeling
A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia
Sketch-Guided Constrained Decoding for Boosting Blackbox Large Language Models without Logit Access
ClickSight: Interpreting Student Clickstreams to Reveal Insights on Learning Strategies via LLMs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.