Sabri Eyuboglu

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updated a model 28 days ago

hazyresearch/cartridge-wauoq23f

Updated 28 days ago • 45

published 2 models 28 days ago

hazyresearch/cartridge-wauoq23f

Updated 28 days ago • 45

sabrieyuboglu/wauoq23f

Updated 28 days ago

upvoted a paper 29 days ago

Cartridges: Lightweight and general-purpose long context representations via self-study

Paper • 2506.06266 • Published Jun 6 • 5

commented a paper 29 days ago

Cartridges: Lightweight and general-purpose long context representations via self-study

Paper • 2506.06266 • Published Jun 6 • 5 •

2

published a dataset about 2 months ago

sabrieyuboglu/qasper-rewrite-gpt-4.1

Viewer • Updated May 11 • 78 • 19

updated 2 datasets about 2 months ago

sabrieyuboglu/qasper-rewrite-gpt-4.1

Viewer • Updated May 11 • 78 • 19

sabrieyuboglu/qasper-rewrite-gpt-4o

Viewer • Updated May 11 • 78 • 21

published a dataset about 2 months ago

sabrieyuboglu/qasper-rewrite-gpt-4o

Viewer • Updated May 11 • 78 • 21

liked a dataset 3 months ago

hazyresearch/based-swde

Viewer • Updated May 19, 2024 • 1.11k • 5.74k • 4

updated a model 8 months ago

sabrieyuboglu/haystacks-a7x4ogap

Updated Oct 31, 2024 • 1

updated a dataset 9 months ago

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

Viewer • Updated Oct 11, 2024 • 128 • 24

liked a dataset 10 months ago

ScalingIntelligence/monkey_business

Viewer • Updated Sep 2, 2024 • 2.88k • 369 • 17

upvoted a paper 11 months ago

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling

Paper • 2407.21787 • Published Jul 31, 2024 • 13

upvoted a collection over 1 year 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, 2024 • 9

authored a paper over 1 year ago

Zoology: Measuring and Improving Recall in Efficient Language Models

Paper • 2312.04927 • Published Dec 8, 2023 • 2

updated a collection over 1 year 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, 2024 • 9

updated a dataset over 1 year ago

hazyresearch/based-swde-deprecated

Viewer • Updated Mar 12, 2024 • 12.4k • 20

updated a collection over 1 year 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, 2024 • 9

updated a dataset over 1 year ago

hazyresearch/fda

Viewer • Updated Mar 12, 2024 • 1.1k • 22 • 1