Aravind Srinivas(@AravSrinivas)
Every millisecond matters. We’re open sourcing the tokenizer we built and deployed on production; th...
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TL;DR · AI Summary
Perplexity 开源其高效的 Unigram 分词器，CPU 利用率降低 5-6 倍，显著减少延迟。
Key Takeaways
- Perplexity 开源 Unigram 分词器，CPU 利用率降低 5-6 倍。
- 小重排器和嵌入器在 GPU 上运行时间仅为单-digit 毫秒。
- 开源分词器有助于提高整体系统效率。
Outline
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- §引言
Perplexity 开源其高效的 Unigram 分词器。
Unigram 分词器显著降低 CPU 利用率，提高系统效率。
- ·技术细节
小重排器和嵌入器在 GPU 上运行时间仅为单-digit 毫秒。
- ·开源贡献
开源分词器有助于社区和开发者。
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- Perplexity Unigram 分词器
Highlights
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We're open-sourcing the Unigram tokenizer we rebuilt to reduce CPU utilization by 5-6x.
Small rerankers and embedders run in single-digit milliseconds on GPU.
CPU tokenization is a meaningful share of total latency.
#Unigram 分词器#Perplexity#CPU 利用率#分词优化#开源项目
Open original articleEvery millisecond matters. We’re open sourcing the tokenizer we built and deployed on production; that’s far efficient than huggingface and sentencepiece.
Quote
Perplexity
@perplexity_ai
9h
We're open-sourcing the Unigram tokenizer we rebuilt to reduce CPU utilization by 5-6x. Small rerankers and embedders run in single-digit milliseconds on GPU, making CPU tokenization a meaningful share of total latency. github.com/perplexityai/p
