https://github.com/allenai/dolma
공식 코드Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models
Tulu 3: Pushing Frontiers in Open Language Model Post-Training
SPECTER: Document-level Representation Learning using Citation-informed Transformers
SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature
SPECTER: Document-level Representation Learning using Citation-informed Transformers
Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
UnifiedQA: Crossing Format Boundaries With a Single QA System
Coarse-to-Fine Memory Matching for Joint Retrieval and Classification
Automatic benchmarking of large multimodal models via iterative experiment programming
Vocabulary-free Image Classification and Semantic Segmentation
Connecting degree and polarity: An artificial language learning study
Leveraging LLM Embeddings for Cross Dataset Label Alignment and Zero Shot Music Emotion Prediction
JamendoMaxCaps: A Large Scale Music-caption Dataset with Imputed Metadata
SynWMD: Syntax-aware Word Mover's Distance for Sentence Similarity Evaluation
Attention-based Contextual Language Model Adaptation for Speech Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.