HMI serves up to 10,000 tenant-specific BERT and GPT instances on one GPU by replacing lower-layer computation with trigram lookup tables and sharing upper layers with per-task adapters.
Experiments on Paraphrase Identification Using Quora Question Pairs Dataset
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
We modeled the Quora question pairs dataset to identify a similar question. The dataset that we use is provided by Quora. The task is a binary classification. We tried several methods and algorithms and different approach from previous works. For feature extraction, we used Bag of Words including Count Vectorizer, and Term Frequency-Inverse Document Frequency with unigram for XGBoost and CatBoost. Furthermore, we also experimented with WordPiece tokenizer which improves the model performance significantly. We achieved up to 97 percent accuracy. Code and Dataset.
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2025 1verdicts
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HMI: Hierarchical Knowledge Management for Efficient Multi-Tenant Inference in Pretrained Language Models
HMI serves up to 10,000 tenant-specific BERT and GPT instances on one GPU by replacing lower-layer computation with trigram lookup tables and sharing upper layers with per-task adapters.