ct2fast-starcoderplus

Papers using or citing this model 4

• FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness 5.6K citations · 2022 · arXiv (Cornell University) · arXiv

  Transformers are slow and memory-hungry on long sequences, since the time and memory complexity of self-attention are quadratic in sequence length. Approximate attention methods have attempted to address this problem by trading off...

• StarCoder: may the source be with you! 1.4K citations · 2023 · arXiv (Cornell University) · arXiv

  The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context length,...

• Fast Transformer Decoding: One Write-Head is All You Need 931 citations · 2019 · arXiv (Cornell University) · arXiv

  Multi-head attention layers, as used in the Transformer neural sequence model, are a powerful alternative to RNNs for moving information across and between sequences. While training these layers is generally fast and simple, due to...

• Efficient Training of Language Models to Fill in the Middle 340 citations · 2022 · arXiv (Cornell University) · arXiv

  We show that autoregressive language models can learn to infill text after we apply a straightforward transformation to the dataset, which simply moves a span of text from the middle of a document to its end. While this data...