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Xlnet Large Cased

Developed by xlnet
XLNet is an unsupervised language representation learning method based on a generalized permutation language modeling objective, using Transformer-XL as the backbone model, excelling in long-context tasks.
Downloads 2,419
Release Time : 3/2/2022

Model Overview

XLNet is an advanced pre-trained language model trained with a generalized permutation language modeling objective, suitable for various natural language processing tasks.

Model Features

Generalized Permutation Language Modeling
Adopts a novel language modeling objective to overcome the limitations of traditional autoregressive models.
Long Context Processing Capability
Based on the Transformer-XL architecture, particularly suitable for long-sequence language tasks.
Multi-task Adaptability
Performs excellently in various tasks such as question answering, natural language inference, and sentiment analysis.

Model Capabilities

Text Feature Extraction
Sequence Classification
Token Classification
Question Answering System

Use Cases

Natural Language Processing
Sentiment Analysis
Analyzes the sentiment orientation of text
Achieves SOTA level in multiple benchmark tests
Question Answering System
Builds a context-based question answering system
Performs excellently on datasets like SQuAD
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