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Research

Ulysses Sequence Parallelism enables million-token training

Researchers at HuggingFace published Ulysses Sequence Parallelism, a technique that splits long token sequences across GPUs to train models on million-token contexts without expanding memory per device.

1 min read

HuggingFace published Ulysses Sequence Parallelism, a distributed training technique that partitions long token sequences across multiple GPUs to enable million-token context windows without proportionally increasing per-device memory consumption.

The core innovation addresses a hard constraint in ...

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Method & sources
Source type
Primary publication (lab/vendor blog) — our analysis + implication
Source link
Hugging Face Blog
Published
UTC
Byline
By the gotcontext.ai team (editorial standards)
Correction?
corrections@gotcontext.ai