microsoft / text-classification updated 5 years ago

deberta-large-mnli

Name: deberta-large-mnli
Author: microsoft

DeBERTa improves the BERT and RoBERTa models using disentangled attention and enhanced mask decoder. It outperforms BERT and RoBERTa on majority of NLU tasks with 80GB training data.

Params

—

Context

512

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252 K

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Commercial use: allowed mit Not gated 1 languages View on Hugging Face ↗

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Specifications

Architecture: DebertaForSequenceClassification
Context length: 512
Vocabulary: 50,265
Layers / heads: 24 / 16
Licence: mit
First seen on the Hub: 2022-03-02
Training datasets: undisclosed
Added to our catalog: 2026-07-28

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