-
Universal Language Model Fine-tuning for Text Classification
Paper • 1801.06146 • Published • 6 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Paper • 2205.14135 • Published • 13 -
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
Paper • 1808.06226 • Published • 1
Collections
Discover the best community collections!
Collections including paper arxiv:1810.04805
-
Attention Is All You Need
Paper • 1706.03762 • Published • 49 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 80 -
Gemini: A Family of Highly Capable Multimodal Models
Paper • 2312.11805 • Published • 44
-
SMOTE: Synthetic Minority Over-sampling Technique
Paper • 1106.1813 • Published • 1 -
Scikit-learn: Machine Learning in Python
Paper • 1201.0490 • Published • 1 -
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Paper • 1406.1078 • Published -
Distributed Representations of Sentences and Documents
Paper • 1405.4053 • Published
-
Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 80 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
Metadata Might Make Language Models Better
Paper • 2211.10086 • Published • 4 -
DecoderLens: Layerwise Interpretation of Encoder-Decoder Transformers
Paper • 2310.03686 • Published • 3
-
Mistral 7B
Paper • 2310.06825 • Published • 46 -
BloombergGPT: A Large Language Model for Finance
Paper • 2303.17564 • Published • 21 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 14
-
Lost in the Middle: How Language Models Use Long Contexts
Paper • 2307.03172 • Published • 38 -
Efficient Estimation of Word Representations in Vector Space
Paper • 1301.3781 • Published • 6 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
Attention Is All You Need
Paper • 1706.03762 • Published • 49
-
Attention Is All You Need
Paper • 1706.03762 • Published • 49 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
Universal Language Model Fine-tuning for Text Classification
Paper • 1801.06146 • Published • 6 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 12
-
Attention Is All You Need
Paper • 1706.03762 • Published • 49 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 16 -
Universal Language Model Fine-tuning for Text Classification
Paper • 1801.06146 • Published • 6 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 12