Sabri Eyuboglu

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updated a model 29 days ago

sabrieyuboglu/haystacks-a7x4ogap

Updated 29 days ago • 121

updated a dataset about 2 months ago

sabrieyuboglu/math-test-llama3.2-1b-n128-l512

Viewer • Updated Oct 11 • 128 • 44

liked a dataset 3 months ago

ScalingIntelligence/monkey_business

Viewer • Updated Sep 2 • 2.88k • 430 • 10

upvoted a paper 3 months ago

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling

Paper • 2407.21787 • Published Jul 31 • 3

upvoted a collection 9 months ago

based

Collection

These language model checkpoints are trained at the 360M and 1.3Bn parameter scales for up to 50Bn tokens on the Pile corpus, for research purposes. • 15 items • Updated Oct 18 • 9

authored a paper 9 months ago

Zoology: Measuring and Improving Recall in Efficient Language Models

Paper • 2312.04927 • Published Dec 8, 2023 • 2

updated a collection 9 months ago

based

Collection

These language model checkpoints are trained at the 360M and 1.3Bn parameter scales for up to 50Bn tokens on the Pile corpus, for research purposes. • 15 items • Updated Oct 18 • 9

updated a dataset 9 months ago

hazyresearch/based-swde-deprecated

Viewer • Updated Mar 12 • 12.4k • 29

updated a collection 9 months ago

based

Collection

These language model checkpoints are trained at the 360M and 1.3Bn parameter scales for up to 50Bn tokens on the Pile corpus, for research purposes. • 15 items • Updated Oct 18 • 9

updated a dataset 9 months ago

hazyresearch/fda

Viewer • Updated Mar 12 • 1.1k • 31 • 1

commented a paper 9 months ago

Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28 • 18 •

12

upvoted a paper 9 months ago

Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28 • 18

updated a collection 9 months ago

based

Collection

These language model checkpoints are trained at the 360M and 1.3Bn parameter scales for up to 50Bn tokens on the Pile corpus, for research purposes. • 15 items • Updated Oct 18 • 9

authored a paper 9 months ago

Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28 • 18

updated a collection 9 months ago

based

Collection

These language model checkpoints are trained at the 360M and 1.3Bn parameter scales for up to 50Bn tokens on the Pile corpus, for research purposes. • 15 items • Updated Oct 18 • 9