Cerebras Systems Enables GPU-Impossible™ Long Sequence Lengths Improving Accuracy in Natural Language Processing Models
Customers can now rapidly train Transformer-style natural language AI models with 20x longer sequences than is possible using traditional computer hardware.
- Customers can now rapidly train Transformer-style natural language AI models with 20x longer sequences than is possible using traditional computer hardware.
- Long sequence lengths enable an NLP model to understand a given word, within a larger and broader context.
- By vastly enlarging the context (the sequence of words within which the target word is understood), Cerebras enables NLP models to demonstrate a more sophisticated understanding of language.
- Training large models with massive data sets and long sequence lengths is an area that the Cerebras CS-2 system, powered by the Wafer-Scale Engine (WSE-2), excels.